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Recent content on R ViewsHugo -- gohugo.ioen-usRStudio, Inc. All Rights Reserved.Wed, 20 Jun 2018 00:00:00 +0000Reading and analysing log files in the RRD database format
https://rviews.rstudio.com/2018/06/20/reading-rrd-files/
Wed, 20 Jun 2018 00:00:00 +0000https://rviews.rstudio.com/2018/06/20/reading-rrd-files/
<p>I have frequent conversations with R champions and Systems Administrators responsible for R, in which they ask how they can measure and analyze the usage of their servers. Among the many solutions to this problem, one of the my favourites is to use an <strong>RRD</strong> database and <strong>RRDtool</strong>.</p>
<p>From <a href="https://en.wikipedia.org/wiki/RRDtool">Wikipedia</a>:</p>
<blockquote>
<p><strong>RRDtool</strong> (<em>round-robin database tool</em>) aims to handle time series data such as network bandwidth, temperatures or CPU load. The data is stored in a <a href="https://en.wikipedia.org/wiki/Circular_buffer">circular buffer</a> based <a href="https://en.wikipedia.org/wiki/Database">database</a>, thus the system storage footprint remains constant over time.</p>
</blockquote>
<p><a href="https://oss.oetiker.ch/rrdtool/index.en.html">RRDtool</a> is a library written in C, with implementations that can also be accessed from the Linux command line. This makes it convenient for system development, but makes it difficult for R users to extract and analyze this data.</p>
<p>I am pleased to announce that I’ve been working on the <code>rrd</code> <a href="https://github.com/andrie/rrd">R package</a> to import RRD files directly into <code>tibble</code> objects, thus making it easy to analyze your metrics.</p>
<p>As an aside, the RStudio Pro products (specifically <a href="https://www.rstudio.com/products/rstudio-server-pro/">RStudio Server Pro</a> and <a href="https://www.rstudio.com/products/connect/">RStudio Connect</a>) also make use of RRD to store metrics – more about this later.</p>
<h2 id="understanding-the-rrd-format-as-an-r-user">Understanding the RRD format as an R user</h2>
<p>The name RRD is an initialism of <strong>R</strong>ound <strong>R</strong>obin <strong>D</strong>atabase. The “round robin” refers to the fact that the database is always fixed in size, and as a new entry enters the database, the oldest entry is discarded. In practical terms, the database collects data for a fixed period of time, and information that is older than the threshold gets removed.</p>
<p><img src="/post/2018-06-21-analysing-rrd-files_files/rra.png" alt="Image from loriotpro(https://bit.ly/2tk2MFa)" /></p>
<p>A second quality of RRD databases is that each datum is stored in different “consolidation data points”, where every data point is an aggregation over time. For example, a data point can represent an average value for the time period, or a maximum over the period. Typical consolidation functions include <code>average</code>, <code>min</code> and <code>max</code>.</p>
<p>The third quality is that every RRD database file typically consists of multiple archives. Each archive measures data for a different time period. For instance, the archives can capture data for intervals of 10 seconds, 30 seconds, 1 minute or 5 minutes.</p>
<p>As an example, here is a description of an RRD file that originated in RStudio Connect:</p>
<pre><code>describe_rrd("rrd_cpu_0")
#> A RRD file with 10 RRA arrays and step size 60
#> [1] AVERAGE_60 (43200 rows)
#> [2] AVERAGE_300 (25920 rows)
#> [3] MIN_300 (25920 rows)
#> [4] MAX_300 (25920 rows)
#> [5] AVERAGE_3600 (8760 rows)
#> [6] MIN_3600 (8760 rows)
#> [7] MAX_3600 (8760 rows)
#> [8] AVERAGE_86400 (1825 rows)
#> [9] MIN_86400 (1825 rows)
#> [10] MAX_86400 (1825 rows)
</code></pre>
<p>This <code>RRD</code> file contains data for the properties of CPU 0 of the system. In this example, the first <code>RRA</code> archive contains averaged metrics for one minute (60s) intervals, while the second <code>RRA</code> measures the same metric, but averaged over five minutes. The same metrics are also available for intervals of one hour and one day.</p>
<p>Notice also that every archive has a different number of rows, representing a different historical period where the data is kept. For example, the <em>per minute</em> data <code>AVERAGE_60</code> is retained for 43,200 periods (12 days) while the <em>daily</em> data <code>MAX_86400</code> is retained for 1,825 periods (5 years).</p>
<p>If you want to know more, please read the excellent <a href="https://oss.oetiker.ch/rrdtool/tut/rrdtutorial.en.html">introduction tutorial</a> to RRD database.</p>
<h2 id="introducing-the-rrd-package">Introducing the <code>rrd</code> package</h2>
<p>Until recently, it wasn’t easy to import RRD files into R. But I was pleased to discover that a <a href="https://www.google-melange.com/archive/gsoc/2014">Google Summer of Code 2014</a> project created a proof-of-concept R package to read these files. The author of this package is <a href="http://plamendimitrov.net/">Plamen Dimitrov</a>, who published the code on <a href="https://github.com/pldimitrov/Rrd">GitHub</a> and also wrote an <a href="http://plamendimitrov.net/blog/2014/08/09/r-package-for-working-with-rrd-files/">explanatory blog post</a>.</p>
<p>Because I had to provide some suggestions to our customers, I decided to update the package, provide some example code, and generally improve the reliability.</p>
<p>The result is not yet on CRAN, but you can install the development version of package from <a href="https://github.com/andrie/rrd">github</a>.</p>
<h3 id="installing-the-package">Installing the package</h3>
<p>To build the package from source, you first need to install <a href="http://oss.oetiker.ch/rrdtool/doc/librrd.en.html">librrd</a>. Installing <a href="http://oss.oetiker.ch/rrdtool/">RRDtool</a> from your Linux package manager will usually also install this library.</p>
<p>Using Ubuntu:</p>
<pre><code class="language-sh">sudo apt-get install rrdtool librrd-dev
</code></pre>
<p>Using RHEL / CentOS:</p>
<pre><code class="language-sh">sudo yum install rrdtool rrdtool-devel
</code></pre>
<p>Once you have the system requirements in place, you can install the development version of the R package from <a href="https://github.com/andrie/rrd">GitHub</a> using:</p>
<pre><code class="language-r"># install.packages("devtools")
devtools::install_github("andrie/rrd")
</code></pre>
<h3 id="limitations">Limitations</h3>
<p>The package is not yet available for Windows.</p>
<h3 id="using-the-package">Using the package</h3>
<p>Once you’ve installed the package, you can start to use it. The package itself contains some built-in RRD files, so you should be able to run the following code directly.</p>
<pre><code class="language-r">library(rrd)
</code></pre>
<h4 id="describing-the-contents-of-a-rrd">Describing the contents of a RRD</h4>
<p>To describe the contents of an RRD file, use <code>describe_rrd()</code>. This function reports information about the names of each archive (RRA) file, the consolidation function, and the number of observations:</p>
<pre><code class="language-r">rrd_cpu_0 <- system.file("extdata/cpu-0.rrd", package = "rrd")
describe_rrd(rrd_cpu_0)
#> A RRD file with 10 RRA arrays and step size 60
#> [1] AVERAGE_60 (43200 rows)
#> [2] AVERAGE_300 (25920 rows)
#> [3] MIN_300 (25920 rows)
#> [4] MAX_300 (25920 rows)
#> [5] AVERAGE_3600 (8760 rows)
#> [6] MIN_3600 (8760 rows)
#> [7] MAX_3600 (8760 rows)
#> [8] AVERAGE_86400 (1825 rows)
#> [9] MIN_86400 (1825 rows)
#> [10] MAX_86400 (1825 rows)
</code></pre>
<h4 id="reading-an-entire-rrd-file">Reading an entire RRD file</h4>
<p>To read an entire RRD file, i.e. all of the RRA archives, use <code>read_rrd()</code>. This returns a list of <code>tibble</code> objects:</p>
<pre><code class="language-r">cpu <- read_rrd(rrd_cpu_0)
str(cpu, max.level = 1)
#> List of 10
#> $ AVERAGE60 :Classes 'tbl_df', 'tbl' and 'data.frame': 43199 obs. of 9 variables:
#> $ AVERAGE300 :Classes 'tbl_df', 'tbl' and 'data.frame': 25919 obs. of 9 variables:
#> $ MIN300 :Classes 'tbl_df', 'tbl' and 'data.frame': 25919 obs. of 9 variables:
#> $ MAX300 :Classes 'tbl_df', 'tbl' and 'data.frame': 25919 obs. of 9 variables:
#> $ AVERAGE3600 :Classes 'tbl_df', 'tbl' and 'data.frame': 8759 obs. of 9 variables:
#> $ MIN3600 :Classes 'tbl_df', 'tbl' and 'data.frame': 8759 obs. of 9 variables:
#> $ MAX3600 :Classes 'tbl_df', 'tbl' and 'data.frame': 8759 obs. of 9 variables:
#> $ AVERAGE86400:Classes 'tbl_df', 'tbl' and 'data.frame': 1824 obs. of 9 variables:
#> $ MIN86400 :Classes 'tbl_df', 'tbl' and 'data.frame': 1824 obs. of 9 variables:
#> $ MAX86400 :Classes 'tbl_df', 'tbl' and 'data.frame': 1824 obs. of 9 variables:
</code></pre>
<p>Since the resulting object is a list of <code>tibble</code> objects, you can easily use R functions to work with an individual archive:</p>
<pre><code class="language-r">names(cpu)
#> [1] "AVERAGE60" "AVERAGE300" "MIN300" "MAX300"
#> [5] "AVERAGE3600" "MIN3600" "MAX3600" "AVERAGE86400"
#> [9] "MIN86400" "MAX86400"
</code></pre>
<p>To inspect the contents of the first archive (<code>AVERAGE60</code>), simply print the object - since it’s a <code>tibble</code>, you get 10 lines of output.</p>
<p>For example, the CPU metrics contains a time stamp and metrics for average <em>user</em> and <em>sys</em> usage, as well as the <a href="https://en.wikipedia.org/wiki/Nice_(Unix)"><em>nice</em></a> value, <em>idle</em> time, <a href="https://en.wikipedia.org/wiki/Interrupt_request_(PC_architecture)"><em>interrupt requests</em></a> and <em>soft interrupt requests</em>:</p>
<pre><code class="language-r">cpu[[1]]
#> # A tibble: 43,199 x 9
#> timestamp user sys nice idle wait irq softirq
#> * <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2018-04-02 12:24:00 0.0104 0.00811 0 0.981 0 0 0
#> 2 2018-04-02 12:25:00 0.0126 0.00630 0 0.979 0 0 0
#> 3 2018-04-02 12:26:00 0.0159 0.00808 0 0.976 0 0 0
#> 4 2018-04-02 12:27:00 0.00853 0.00647 0 0.985 0 0 0
#> 5 2018-04-02 12:28:00 0.0122 0.00999 0 0.978 0 0 0
#> 6 2018-04-02 12:29:00 0.0106 0.00604 0 0.983 0 0 0
#> 7 2018-04-02 12:30:00 0.0147 0.00427 0 0.981 0 0 0
#> 8 2018-04-02 12:31:00 0.0193 0.00767 0 0.971 0 0 0
#> 9 2018-04-02 12:32:00 0.0300 0.0274 0 0.943 0 0 0
#> 10 2018-04-02 12:33:00 0.0162 0.00617 0 0.978 0 0 0
#> # ... with 43,189 more rows, and 1 more variable: stolen <dbl>
</code></pre>
<p>Since the data is in <code>tibble</code> format, you can easily extract specific data, e.g., the last values of the system usage:</p>
<pre><code class="language-r">
tail(cpu$AVERAGE60$sys)
#> [1] 0.0014390667 0.0020080000 0.0005689333 0.0000000000 0.0014390667
#> [6] 0.0005689333
</code></pre>
<h4 id="reading-only-a-single-archive">Reading only a single archive</h4>
<p>The underlying code in the <code>rrd</code> package is written in C, and is therefore blazingly fast. Reading an entire RRD file takes a fraction of a second, but sometimes you may want to extract a specific RRA archive immediately.</p>
<p>To read a single RRA archive from an RRD file, use <code>read_rra()</code>. To use this function, you must specify several arguments that define the specific data to retrieve. This includes the consolidation function (e.g., <code>"AVERAGE"</code>) and time step (e.g., <code>60</code>). You must also specify either the <code>start</code> time or the number of steps, <code>n_steps</code>.</p>
<p>In this example, I extract the average for one-minute periods (<code>step = 60</code>) for one day (<code>n_steps = 24 * 60</code>):</p>
<pre><code class="language-r">end_time <- as.POSIXct("2018-05-02") # timestamp with data in example
avg_60 <- read_rra(rrd_cpu_0, cf = "AVERAGE", step = 60, n_steps = 24 * 60,
end = end_time)
avg_60
#> # A tibble: 1,440 x 9
#> timestamp user sys nice idle wait irq softirq
#> * <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2018-05-01 00:01:00 0.00458 0.00201 0 0.992 0 0 0
#> 2 2018-05-01 00:02:00 0.00258 0.000570 0 0.996 0 0 0
#> 3 2018-05-01 00:03:00 0.00633 0.00144 0 0.992 0 0 0
#> 4 2018-05-01 00:04:00 0.00515 0.00201 0 0.991 0 0 0
#> 5 2018-05-01 00:05:00 0.00402 0.000569 0 0.995 0 0 0
#> 6 2018-05-01 00:06:00 0.00689 0.00144 0 0.992 0 0 0
#> 7 2018-05-01 00:07:00 0.00371 0.00201 0 0.993 0.00144 0 0
#> 8 2018-05-01 00:08:00 0.00488 0.00201 0 0.993 0.000569 0 0
#> 9 2018-05-01 00:09:00 0.00748 0.000568 0 0.992 0 0 0
#> 10 2018-05-01 00:10:00 0.00516 0 0 0.995 0 0 0
#> # ... with 1,430 more rows, and 1 more variable: stolen <dbl>
</code></pre>
<h4 id="plotting-the-results">Plotting the results</h4>
<p>The original <code>RRDTool</code> library for Linux contains some functions to <a href="https://oss.oetiker.ch/rrdtool/gallery/index.en.html">easily plot</a> the RRD data, a feature that distinguishes RRD from many other databases.</p>
<p>However, R already has very rich plotting capability, so the <code>rrd</code> R package doesn’t expose any specific plotting functions.</p>
<p>For example, you can easily plot these data using your favourite packages, like <code>ggplot2</code>:</p>
<pre><code class="language-r">library(ggplot2)
ggplot(avg_60, aes(x = timestamp, y = user)) +
geom_line() +
stat_smooth(method = "loess", span = 0.125, se = FALSE) +
ggtitle("CPU0 usage, data read from RRD file")
</code></pre>
<p><img src="/post/2018-06-21-analysing-rrd-files_files/ggplot.png" alt="" /></p>
<h2 id="getting-the-rrd-files-from-rstudio-server-pro-and-rstudio-connect">Getting the RRD files from RStudio Server Pro and RStudio Connect</h2>
<p>As I mentioned in the introduction, both <a href="https://www.rstudio.com/products/rstudio-server-pro/">RStudio Server Pro</a> and <a href="https://www.rstudio.com/products/connect/">RStudio Connect</a> use RRD to store metrics. In fact, these metrics are used to power the administration dashboard of these products.</p>
<p>This means that often the easiest solution is simply to enable the admin dashboard and view the information there.</p>
<p><img src="/post/2018-06-21-analysing-rrd-files_files/rsp_admin_dashboard.png" alt="RStudio Server Pro admin dashboard" /></p>
<p>However, sometimes R users and system administrators have a need to analyze the metrics in more detail, so in this section, I discuss where you can find the files for analysis.</p>
<p>The administration guides for these products explain where to find the metrics files:</p>
<ul>
<li>The admin guide for <strong>RStudio Server Pro</strong> discusses metrics in this in section <a href="http://docs.rstudio.com/ide/server-pro/auditing-and-monitoring.html#monitoring-configuration">8.2 Monitoring Configuration</a>.
<ul>
<li>By default, the metrics are stored at <code>/var/lib/rstudio-server/monitor/rrd</code>, although this path is configurable by the server administrator</li>
<li>RStudio Server Pro stores system metrics as well as user metrics</li>
</ul></li>
<li><strong>RStudio Connect</strong> discusses metrics in section <a href="http://docs.rstudio.com/connect/admin/historical-information.html#metrics">16.1 Historical Metrics</a>
<ul>
<li>The default path for metrics logs is <code>/var/lib/rstudio-connect/metrics</code>, though again, this is configurable by the server administrator.</li>
</ul></li>
</ul>
<pre><code class="language-r">rsc <- "/var/lib/rstudio-connect/metrics/rrd"
rsp <- "/var/lib/rstudio-server/monitor/rrd"
</code></pre>
<p>If you want to analyze these files, it is best to copy the files to a different location. The security and permissions on both products are configured in such a way that it’s not possible to read the files while they are in the original folder. Therefore, we recommend that you copy the files to a different location and do the analysis there.</p>
<h3 id="warning-about-using-the-rstudio-connect-rrd-files">Warning about using the RStudio Connect RRD files:</h3>
<p>The RStudio Connect team is actively planning to change the way content-level metrics are stored, so data related to shiny apps, markdown reports, etc. will likely look different in a future release.</p>
<p>To be clear:</p>
<ul>
<li>The schemas might change</li>
<li>RStudio Connect may stop tracking some metrics</li>
<li>It’s also possible that the entire mechanism might change</li>
</ul>
<p>The only guarantees that we make in RStudio Connect are around the data that we actually surface:</p>
<ul>
<li>server-wide user counts</li>
<li>RAM</li>
<li>CPU data</li>
</ul>
<p>This means that if you analyze RRD files, you should be aware that <strong>the entire mechanism for storing metrics might change in future</strong>.</p>
<h3 id="additional-caveat">Additional caveat</h3>
<ul>
<li>The metrics collection process runs in a sandboxed environment, and it is not possible to publish a report to RStudio Connect that reads the metrics directly. If you want to automate a process to read the Connect metrics, you will have to set up a <a href="https://en.wikipedia.org/wiki/Cron">cron</a> job to copy the files to a different location, and run the analysis against the copied files. (Also, re-read the warning that everything might change!)</li>
</ul>
<h3 id="example">Example</h3>
<p>In the following worked example, I copied some <code>rrd</code> files that originated in RStudio Connect to a different location on disk, and stored this in a <a href="https://github.com/rstudio/config"><code>config</code></a> file.</p>
<p>First, list the file names:</p>
<pre><code class="language-r">config <- config::get()
rrd_location <- config$rrd_location
rrd_location %>%
list.files() %>%
tail(20)
</code></pre>
<pre><code>## [1] "content-978.rrd" "content-986.rrd" "content-98.rrd"
## [4] "content-990.rrd" "content-995.rrd" "content-998.rrd"
## [7] "cpu-0.rrd" "cpu-1.rrd" "cpu-2.rrd"
## [10] "cpu-3.rrd" "license-users.rrd" "network-eth0.rrd"
## [13] "network-lo.rrd" "system-CPU.rrd" "system.cpu.usage.rrd"
## [16] "system.load.rrd" "system.memory.rrd" "system-RAM.rrd"
## [19] "system.swap.rrd" "system-SWAP.rrd"
</code></pre>
<p>The file names indicated that RStudio Connect collects metrics for the system (CPU, RAM, etc.), as well as for every piece of published content.</p>
<p>To look at the system load, first describe the contents of the <code>"system.load.rrd"</code> file:</p>
<pre><code class="language-r">sys_load <- file.path(rrd_location, "system.load.rrd")
describe_rrd(sys_load)
</code></pre>
<pre><code>## A RRD file with 10 RRA arrays and step size 60
## [1] AVERAGE_60 (43200 rows)
## [2] AVERAGE_300 (25920 rows)
## [3] MIN_300 (25920 rows)
## [4] MAX_300 (25920 rows)
## [5] AVERAGE_3600 (8760 rows)
## [6] MIN_3600 (8760 rows)
## [7] MAX_3600 (8760 rows)
## [8] AVERAGE_86400 (1825 rows)
## [9] MIN_86400 (1825 rows)
## [10] MAX_86400 (1825 rows)
</code></pre>
<p>This output tells you that metrics are collected every 60 seconds (one minute), and then in selected multiples (1 minute, 5 minutes, 1 hour and 1 day.) You can also tell that the consolidation functions are <code>average</code>, <code>min</code> and <code>max</code>.</p>
<p>To extract one month of data, averaged at 5-minute intervals use <code>step = 300</code>:</p>
<pre><code class="language-r">dat <- read_rra(sys_load, cf = "AVERAGE", step = 300L, n_steps = (3600 / 300) * 24 * 30)
dat
</code></pre>
<pre><code>## # A tibble: 8,640 x 4
## timestamp `1min` `5min` `15min`
## * <dttm> <dbl> <dbl> <dbl>
## 1 2018-05-10 19:10:00 0.0254 0.0214 0.05
## 2 2018-05-10 19:15:00 0.263 0.153 0.0920
## 3 2018-05-10 19:20:00 0.0510 0.117 0.101
## 4 2018-05-10 19:25:00 0.00137 0.0509 0.0781
## 5 2018-05-10 19:30:00 0 0.0168 0.0534
## 6 2018-05-10 19:35:00 0 0.01 0.05
## 7 2018-05-10 19:40:00 0.0146 0.0166 0.05
## 8 2018-05-10 19:45:00 0.00147 0.0115 0.05
## 9 2018-05-10 19:50:00 0.0381 0.0306 0.05
## 10 2018-05-10 19:55:00 0.0105 0.018 0.05
## # ... with 8,630 more rows
</code></pre>
<p>It is very easy to plot this using your preferred plotting package, e.g., <code>ggplot2</code>:</p>
<pre><code class="language-r">ggplot(dat, aes(x = timestamp, y = `5min`)) +
geom_line() +
stat_smooth(method = "loess", span = 0.125)
</code></pre>
<p><img src="/post/2018-06-21-analysing-rrd-files_files/ggplot.png" alt="" /></p>
<h2 id="conclusion">Conclusion</h2>
<p>The <code>rrd</code> package, available from <a href="https://github.com/andrie/rrd">GitHub</a>, makes it very easy to read metrics stored in the RRD database format. Reading an archive is very quick, and your resulting data is a <code>tibble</code> for an individual archive, or a list of <code>tibble</code>s for the entire file.</p>
<p>This makes it easy to analyze your data using the <code>tidyverse</code> packages, and to plot the information.</p>
<script>window.location.href='https://rviews.rstudio.com/2018/06/20/reading-rrd-files/';</script>
Player Data for the 2018 FIFA World Cup
https://rviews.rstudio.com/2018/06/14/player-data-for-the-2018-fifa-world-cup/
Thu, 14 Jun 2018 00:00:00 +0000https://rviews.rstudio.com/2018/06/14/player-data-for-the-2018-fifa-world-cup/
<p>The World Cup starts today! The tournament which runs from June 14 through July 15 is probably the most popular sporting event in the world. if you are a soccer fan, you know that learning about the players and their teams and talking about it all with your friends greatly enhances the experience. In this post, I will show you how to gather and explore data for the 736 players from the 32 teams at the 2018 FIFA World Cup. Have fun and enjoy the games. I will be watching with you.</p>
<div id="download-player-data" class="section level2">
<h2>Download Player Data</h2>
<div id="official-pdf" class="section level3">
<h3>Official PDF</h3>
<p>FIFA has made several official player lists available, conveniently changing the format each time. For this exercise, I use the one from early June. The <a href="https://CRAN.R-project.org/package=tabulizer">tabulizer package</a> makes extracting information from tables included in a PDF document relatively easy. (The other (later) version of the official PDF is <a href="https://github.com/davidkane9/wc18/raw/master/fifa_player_list_2.pdf">here</a>. Strangely, the weight variable has been dropped.)</p>
<pre class="r"><code>suppressMessages(library(tidyverse))
library(stringr)
suppressMessages(library(lubridate))
suppressMessages(library(cowplot))
# Note that I set warnings to FALSE because of some annoying (and intermittent)
# issues with RJavaTools.
library(tabulizer)
url <- "https://github.com/davidkane9/wc18/raw/master/fifa_player_list_1.pdf"
out <- extract_tables(url, output = "data.frame")</code></pre>
<p>We now have a 32 element list, each item a data frame of information about the 23 players on each team. Let’s combine this information into a single tidy tibble.</p>
<pre class="r"><code># Note how bind_rows() makes it very easy to combine a list of compatible
# dataframes.
pdf_data <- bind_rows(out) %>%
as_tibble() %>%
# Make the variable names more tidy-like.
rename(team = Team,
number = X.,
position = Pos.,
name = FIFA.Popular.Name,
birth_date = Birth.Date,
shirt_name = Shirt.Name,
club = Club,
height = Height,
weight = Weight) %>%
# Country names are contentious issues. I modify two names because I will
# later need to merge this tibble with data from Wikipedia, which uses
# different names.
mutate(team = case_when(
team == "Korea Republic" ~ "South Korea",
team == "IR Iran" ~ "Iran",
TRUE ~ team)) %>%
# league and club should be separate variables. We also want birth_date to be
# a date and to have an age variable already calculated.
mutate(birth_date = dmy(birth_date),
league = str_sub(club, -4, -2),
club = str_sub(club, end = -7),
age = interval(birth_date, "2018-06-14") / years(1))</code></pre>
<p>Here is a sample of the data:</p>
<pre><code>## # A tibble: 10 x 10
## team number position birth_date shirt_name club height weight league age
## <chr> <int> <chr> <date> <chr> <chr> <int> <int> <chr> <dbl>
## 1 Denmark 3 DF 1992-08-03 VESTERGAARD VfL Bor… 200 98 GER 25.9
## 2 Argentina 18 DF 1990-07-13 SALVIO SL Benf… 167 69 POR 27.9
## 3 Croatia 15 DF 1996-09-17 ĆALETA-CAR FC Red … 192 89 AUT 21.7
## 4 Croatia 21 DF 1989-04-29 VIDA Besikta… 184 76 TUR 29.1
## 5 Japan 3 DF 1992-12-11 SHOJI Kashima… 182 74 JPN 25.5
## 6 Colombia 7 FW 1986-09-08 BACCA Villarr… 181 77 ESP 31.8
## 7 Iceland 10 MF 1989-09-08 G. SIGURDSSON Everton… 186 82 ENG 28.8
## 8 Germany 17 DF 1988-09-03 BOATENG FC Baye… 192 90 GER 29.8
## 9 Poland 4 DF 1986-04-21 CIONEK SPAL Fe… 184 81 ITA 32.1
## 10 Uruguay 9 FW 1987-01-24 L. SUAREZ FC Barc… 182 85 ESP 31.4</code></pre>
<p>Perform some error checking.</p>
<pre class="r"><code>stopifnot(length(unique(pdf_data$team)) == 32) # There are 32 teams.
stopifnot(all(range(table(pdf_data$team)) == 23)) # Each team has 23 players.
stopifnot(pdf_data %>%
filter(position == "GK") %>%
group_by(team) %>%
tally() %>%
filter(n != 3) %>%
nrow() == 0) # All teams have 3 goal keepers.
stopifnot(all(pdf_data$position %in%
c("GK", "DF", "MF", "FW"))) # All players assigned to 1 of 4 positions.</code></pre>
</div>
<div id="wikipedia-data" class="section level3">
<h3>Wikipedia Data</h3>
<p>Wikipedia includes other player information which might be interesting, especially the number of caps for each player. A “cap” is an appearance in a game for the national team. The <a href="https://CRAN.R-project.org/package=rvest">rvest package</a> makes scraping data from Wikipedia fairly easy.</p>
<pre class="r"><code>suppressMessages(library(rvest))
html <- read_html("https://en.wikipedia.org/wiki/2018_FIFA_World_Cup_squads")
# Once we have read in all the html, we need to identify the location of the
# data we want. The rvest vignette provides guidance, but the key trick is the
# use of SelectorGadget to find the correct CSS node.
# First, we need the country and the shirt number of each player so that we can
# merge this data with that from the PDF.
country <- html_nodes(html, ".mw-headline") %>%
html_text() %>%
as_tibble() %>%
filter(! str_detect(value, "Group")) %>%
slice(1:32)
number <- html_nodes(html, ".plainrowheaders td:nth-child(1)") %>%
html_text()
# We don't need the name of each player but I like to grab it, both because I
# prefer the Wikipedia formatting and to use this as a cross-check on the
# accuracy of our country/number merge.
name <- html_nodes(html, "th a") %>%
html_text() %>%
as_tibble() %>%
filter(! str_detect(value, "^captain$")) %>%
slice(1:736)
# cap is the variable we care about, but Wikipedia page also includes the number
# of goals that each player has scored for the national team. Try adding that
# information on your own.
caps <- html_nodes(html, ".plainrowheaders td:nth-child(5)") %>%
html_text()
# Create a tibble. Note that we are relying on all the vectors being in the
# correct order.
wiki_data <- tibble(
number = as.numeric(number),
name = name$value,
team = rep(country$value, each = 23),
caps = as.numeric(caps))
# I prefer the name from Wikipedia. Exercise for the reader: How might we use
# name (from Wikipedia) and shirt_name (from the PDF) to confirm that we have
# lined up the data correctly?
x <- left_join(select(pdf_data, -name), wiki_data, by = c("team", "number"))</code></pre>
</div>
</div>
<div id="data-exploration" class="section level2">
<h2>Data Exploration</h2>
<p>With this information, there are a variety of topics to explore.</p>
<div id="birth-month" class="section level3">
<h3>Birth Month</h3>
<p>For the entire sample of 736 players, there is a clear birth month effect, visible both when looking at calendar months and when aggregating to calendar quarters. Players are much more likely to have birthdays earlier in the year. The most common explanation is that players born in January have an advantage over players born in December (when both are born in the same calendar year) because the former will be older than the later whenever they are competing for spots on the same age-group team, given that the cut-offs are always (?) December 31. This advantage in youth soccer bleeds into adult soccer because of the extra opportunities it provides for expert coaching. (See “<a href="https://www.nytimes.com/2006/05/07/magazine/07wwln_freak.html">A Star Is Made</a>,” by Stephen J. Dubner and Steven D. Levitt, May 7, 2006, <em>New York Times Magazine</em>.)</p>
<p><img src="/post/2018-06-12-player-data-for-the-2018-fifa-world-cup_files/figure-html/unnamed-chunk-6-1.png" width="672" /></p>
<p>Strangely, the effect is only true for players who will be 25 and over at the start of the World Cup, about 75% of the sample.</p>
<p><img src="/post/2018-06-12-player-data-for-the-2018-fifa-world-cup_files/figure-html/unnamed-chunk-7-1.png" width="672" /></p>
<p>Why would that be true? Note that there are many fewer players starting the tournament at age 24 than one might expect:</p>
<p><img src="/post/2018-06-12-player-data-for-the-2018-fifa-world-cup_files/figure-html/unnamed-chunk-8-1.png" width="672" /></p>
<p>Are the “missing” score or so 24 year-olds a sign of something meaningful or random noise?</p>
</div>
<div id="team-quality" class="section level3">
<h3>Team Quality</h3>
<p>We don’t have good measures of player (or team) quality in this data. But we do know if an individual plays for a team in one of the countries which host the five highest quality leagues: England (ENG), Spain (ESP), Germany (GER), Italy (58) and France (49). (It is no coincidence that these leagues account for the largest share of the players.)</p>
<pre class="r"><code>x %>%
group_by(league) %>%
tally() %>%
arrange(desc(n))</code></pre>
<pre><code>## # A tibble: 55 x 2
## league n
## <chr> <int>
## 1 ENG 124
## 2 ESP 81
## 3 GER 67
## 4 ITA 58
## 5 FRA 49
## 6 RUS 36
## 7 KSA 30
## 8 MEX 22
## 9 TUR 22
## 10 POR 19
## # ... with 45 more rows</code></pre>
<p>Any World Cup team with very few players who play in these 5 leagues is unlikely to be a good team. The best leagues have teams with so much money that they (almost) always are able to hire the best players. The vast majority of players in, for example, the Saudi Arabian or Turkish leagues are not wanted by any team in the best leagues. So, one measure of team quality is the percentage of players who play for teams in those 5 elite leagues. Here are the top 8 and bottom 4:</p>
<pre class="r"><code>x %>%
group_by(team) %>%
summarise(elite = mean(league %in%
c("ENG", "ESP", "GER", "ITA", "FRA"))) %>%
arrange(desc(elite)) %>%
slice(c(1:8, 29:32))</code></pre>
<pre><code>## # A tibble: 12 x 2
## team elite
## <chr> <dbl>
## 1 England 1
## 2 France 1
## 3 Germany 1
## 4 Spain 1
## 5 Belgium 0.826
## 6 Switzerland 0.826
## 7 Senegal 0.783
## 8 Brazil 0.739
## 9 Iran 0.0435
## 10 Panama 0.0435
## 11 Peru 0.0435
## 12 Russia 0.0435</code></pre>
<p>This measure captures the fact that teams like England, France, Spain and Germany are likely to do well while teams like Iran, Panama and Peru are not. Russia, as the host country, is a more difficult case. There are many problems with this analysis. Feel free to point them out in the comments. A better approach would look at the quality of the clubs that individuals play for or, even better, at measures of individual player quality.</p>
<p>What can you do with this data?</p>
<p>David Kane teaches at <a href="https://www.harvard.edu">Harvard University</a> and co-organizes the <a href="https://www.meetup.com/Boston-useR/">Boston R User Group</a>.</p>
</div>
</div>
<script>window.location.href='https://rviews.rstudio.com/2018/06/14/player-data-for-the-2018-fifa-world-cup/';</script>
Monte Carlo Part Two
https://rviews.rstudio.com/2018/06/13/monte-carlo-part-two/
Wed, 13 Jun 2018 00:00:00 +0000https://rviews.rstudio.com/2018/06/13/monte-carlo-part-two/
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<p>In a <a href="https://rviews.rstudio.com/2018/06/05/monte-carlo/">previous post</a>, we reviewed how to set up and run a Monte Carlo (MC) simulation of future portfolio returns and growth of a dollar. Today, we will run that simulation many, many, times and then visualize the results.</p>
<p>Our ultimate goal is to build a Shiny app that allows an end user to build a custom portfolio, simulate returns, and visualize the results. If you just can’t wait, a link to the final Shiny app is available <a href="http://www.reproduciblefinance.com/shiny/monte-carlo-simulation/">here</a>.</p>
<p>This post builds off the work we did previously. I won’t go through the logic again, but the code for building a portfolio, calculating returns, mean and standard deviation of returns, and using them for a simulation is here:</p>
<pre class="r"><code>library(tidyquant)
library(tidyverse)
library(timetk)
library(broom)
library(highcharter)
symbols <- c("SPY","EFA", "IJS", "EEM","AGG")
prices <-
getSymbols(symbols, src = 'yahoo',
from = "2012-12-31",
to = "2017-12-31",
auto.assign = TRUE, warnings = FALSE) %>%
map(~Ad(get(.))) %>%
reduce(merge) %>%
`colnames<-`(symbols)
w <- c(0.25, 0.25, 0.20, 0.20, 0.10)
asset_returns_long <-
prices %>%
to.monthly(indexAt = "lastof", OHLC = FALSE) %>%
tk_tbl(preserve_index = TRUE, rename_index = "date") %>%
gather(asset, returns, -date) %>%
group_by(asset) %>%
mutate(returns = (log(returns) - log(lag(returns)))) %>%
na.omit()
portfolio_returns_tq_rebalanced_monthly <-
asset_returns_long %>%
tq_portfolio(assets_col = asset,
returns_col = returns,
weights = w,
col_rename = "returns",
rebalance_on = "months")
mean_port_return <-
mean(portfolio_returns_tq_rebalanced_monthly$returns)
stddev_port_return <-
sd(portfolio_returns_tq_rebalanced_monthly$returns)
simulation_accum_1 <- function(init_value, N, mean, stdev) {
tibble(c(init_value, 1 + rnorm(N, mean, stdev))) %>%
`colnames<-`("returns") %>%
mutate(growth =
accumulate(returns,
function(x, y) x * y)) %>%
select(growth)
}</code></pre>
<p>That code allows us to run one simulation of the growth of a dollar over the next 10 years, with the <code>simulation_accum_1()</code> that we built for that purpose. Today, we will review how to run 51 simulations, though we could choose any number (and our Shiny application allows an end user to do just that).</p>
<p>First, we need an empty matrix with 51 columns, an initial value of $1, and intuitive column names.</p>
<p>We will use the <code>rep()</code> function to create 51 columns with a 1 as the value, and <code>set_names()</code> to name each column with the appropriate simulation number.</p>
<pre class="r"><code>sims <- 51
starts <-
rep(1, sims) %>%
set_names(paste("sim", 1:sims, sep = ""))</code></pre>
<p>Take a peek at <code>starts</code> to see what we just created, and how it can house our simulations.</p>
<pre class="r"><code>head(starts)</code></pre>
<pre><code>sim1 sim2 sim3 sim4 sim5 sim6
1 1 1 1 1 1 </code></pre>
<pre class="r"><code>tail(starts)</code></pre>
<pre><code>sim46 sim47 sim48 sim49 sim50 sim51
1 1 1 1 1 1 </code></pre>
<p>51 columns, with a value of 1 in one row. This is where we will store the results of the 51 simulations.</p>
<p>Now, we want to apply <code>simulation_accum_1</code> to each of the 51 columns of the <code>starts</code> matrix, and we will do that using the <code>map_dfc()</code> function from the <code>purrr</code> package.</p>
<p><code>map_dfc()</code> takes a vector - in this case, the columns of <code>starts</code> - and applies a function to it. By appending <code>dfc()</code> to the <code>map_</code> function, we are asking the function to store each of its results as the column of a data frame (<code>map_df()</code> does the same thing, but stores results in the rows of a data frame). After running the code below, we will have a data frame with 51 columns, one for each of our simulations.</p>
<p>We also need to choose how many months to simulate (the N argument to our simulation function) and supply the distribution parameters as we did before. We do not supply the <code>init_value</code> argument because the <code>init_value</code> is 1, that same 1 that is already in the 51 columns.</p>
<pre class="r"><code>monte_carlo_sim_51 <-
map_dfc(starts,
simulation_accum_1,
N = 120,
mean = mean_port_return,
stdev = stddev_port_return)
tail(monte_carlo_sim_51 %>% select(growth1, growth2,
growth49, growth50), 3)</code></pre>
<pre><code># A tibble: 3 x 4
growth1 growth2 growth49 growth50
<dbl> <dbl> <dbl> <dbl>
1 1.81 1.38 2.32 1.80
2 1.84 1.37 2.38 1.84
3 1.82 1.33 2.39 1.82</code></pre>
<p>Have a look at the results. We now have 51 simulations of the growth of a dollar, and we simulated that growth over 120 months; however, the results are missing a piece that we need for visualization, namely a <code>month</code> column.</p>
<p>Let’s add that <code>month</code> column with <code>mutate()</code> and give it the same number of rows as our data frame. These are months out into the future. We will use <code>mutate(month = seq(1:nrow(.)))</code>, and then clean up the column names. <code>nrow()</code> is equal to the number of rows in our object. If we were to change to 130 simulations, that would generate 130 rows, and <code>nrow()</code> would be equal to 130.</p>
<pre class="r"><code>monte_carlo_sim_51 <-
monte_carlo_sim_51 %>%
mutate(month = seq(1:nrow(.))) %>%
select(month, everything()) %>%
`colnames<-`(c("month", names(starts))) %>%
mutate_all(funs(round(., 2)))
tail(monte_carlo_sim_51 %>% select(month, sim1, sim2,
sim49, sim50), 3)</code></pre>
<pre><code># A tibble: 3 x 5
month sim1 sim2 sim49 sim50
<dbl> <dbl> <dbl> <dbl> <dbl>
1 119 2.16 1.81 1.46 2.32
2 120 2.28 1.84 1.46 2.38
3 121 2.26 1.82 1.46 2.39</code></pre>
<p>We have accomplished our goal of running 51 simulations, and could head to data visualization now, but let’s explore an alternative method using the the <code>rerun()</code> function from <code>purrr</code>. As its name implies, this function will “rerun” another function, and we stipulate how many times to do that by setting <code>.n = number of times to rerun</code>. For example to run the <code>simulation_accum_1</code> function 5 times, we would set the following:</p>
<pre class="r"><code>monte_carlo_rerun_5 <-
rerun(.n = 5,
simulation_accum_1(1,
120,
mean_port_return,
stddev_port_return))</code></pre>
<p>That returned a list of 5 data frames, or 5 simulations. We can look at the first few rows of each data frame by using <code>map(..., head)</code>.</p>
<pre class="r"><code>map(monte_carlo_rerun_5, head)</code></pre>
<pre><code>[[1]]
# A tibble: 6 x 1
growth
<dbl>
1 1
2 0.983
3 0.965
4 0.946
5 0.967
6 0.962
[[2]]
# A tibble: 6 x 1
growth
<dbl>
1 1
2 0.980
3 0.975
4 0.964
5 0.969
6 0.914
[[3]]
# A tibble: 6 x 1
growth
<dbl>
1 1
2 1.03
3 0.997
4 0.979
5 1.04
6 1.04
[[4]]
# A tibble: 6 x 1
growth
<dbl>
1 1
2 0.974
3 0.962
4 0.943
5 0.942
6 0.963
[[5]]
# A tibble: 6 x 1
growth
<dbl>
1 1
2 0.990
3 1.02
4 1.06
5 1.12
6 1.13 </code></pre>
<p>Let’s consolidate that list of data frames to one <code>tibble</code>. We start by collapsing to vectors with <code>simplify_all()</code>, then add nicer names with the <code>names()</code> function and finally coerce to tibble with <code>as_tibble()</code>. Let’s run it 51 times to match our previous results.</p>
<pre class="r"><code>reruns <- 51
monte_carlo_rerun_51 <-
rerun(.n = reruns,
simulation_accum_1(1,
120,
mean_port_return,
stddev_port_return)) %>%
simplify_all() %>%
`names<-`(paste("sim", 1:reruns, sep = " ")) %>%
as_tibble() %>%
mutate(month = seq(1:nrow(.))) %>%
select(month, everything())
tail(monte_carlo_rerun_51 %>% select(`sim 1`, `sim 2`,
`sim 49`, `sim 50`), 3)</code></pre>
<pre><code># A tibble: 3 x 4
`sim 1` `sim 2` `sim 49` `sim 50`
<dbl> <dbl> <dbl> <dbl>
1 1.99 1.97 3.66 2.20
2 2.00 1.86 3.68 2.25
3 2.02 1.95 3.78 2.18</code></pre>
<p>Now we have two objects holding the results of 51 simulations, <code>monte_carlo_rerun_51</code> and <code>monte_carlo_sim_51</code>.</p>
<p>Each has 51 columns of simulations and 1 column of months. Note that we have 121 rows because we started with an initial value of 1, and then simulated returns over 120 months.</p>
<p>Now let’s get to visualization with <code>ggplot()</code> and visualize the results in <code>monte_carlo_sim_51</code>. The same code flows for visualization would also apply to <code>monte_carlo_rerun_51</code>, but we will run them for only <code>monte_carlo_sim_51</code> here.</p>
<p>We start with a chart of all 51 simulations, and assign a different color to each one by setting <code>ggplot(aes(x = month, y = growth, color = sim))</code>. <code>ggplot()</code> will automatically generate a legend for all 51 time series, but that gets quite crowded. We will suppress the legend with <code>theme(legend.position = "none")</code>.</p>
<pre class="r"><code>monte_carlo_sim_51 %>%
gather(sim, growth, -month) %>%
group_by(sim) %>%
ggplot(aes(x = month, y = growth, color = sim)) +
geom_line() +
theme(legend.position="none")</code></pre>
<p><img src="/post/2018-06-12-monte-carlo-part-2_files/figure-html/unnamed-chunk-9-1.png" width="672" /></p>
<p>We can check the minimum, maximum and median simulation with the <code>summarise()</code> function here.</p>
<pre class="r"><code>sim_summary <-
monte_carlo_sim_51 %>%
gather(sim, growth, -month) %>%
group_by(sim) %>%
summarise(final = last(growth)) %>%
summarise(
max = max(final),
min = min(final),
median = median(final))
sim_summary</code></pre>
<pre><code># A tibble: 1 x 3
max min median
<dbl> <dbl> <dbl>
1 4.81 1.31 2.3</code></pre>
<p>We can clean up our original visualization by including only the max, min and median that were just calculated.</p>
<pre class="r"><code>monte_carlo_sim_51 %>%
gather(sim, growth, -month) %>%
group_by(sim) %>%
filter(
last(growth) == sim_summary$max ||
last(growth) == sim_summary$median ||
last(growth) == sim_summary$min) %>%
ggplot(aes(x = month, y = growth)) +
geom_line(aes(color = sim)) </code></pre>
<p><img src="/post/2018-06-12-monte-carlo-part-2_files/figure-html/unnamed-chunk-11-1.png" width="672" /></p>
<p>Now let’s port our results over to <code>highcharter</code>, but in a major departure from our usual code flow, we will pass a tidy <code>tibble</code> instead of an <code>xts</code> object.</p>
<p>Our first step is to convert the data from wide to long tidy format with the <code>gather()</code> function.</p>
<pre class="r"><code>mc_gathered <-
monte_carlo_sim_51 %>%
gather(sim, growth, -month) %>%
group_by(sim)
head(mc_gathered)</code></pre>
<pre><code># A tibble: 6 x 3
# Groups: sim [1]
month sim growth
<dbl> <chr> <dbl>
1 1 sim1 1
2 2 sim1 0.99
3 3 sim1 1.01
4 4 sim1 1.06
5 5 sim1 1.08
6 6 sim1 1.1 </code></pre>
<p>We can now pass this <code>tibble</code> directly to the <code>hchart()</code> function, specify the type of chart as <code>line</code>, and then work with a similar grammar to <code>ggplot()</code>. The difference is we use <code>hcaes</code>, which stands for <code>highcharter aesthetic</code>, instead of <code>aes</code>.</p>
<pre class="r"><code># This takes a few seconds to run
hchart(mc_gathered,
type = 'line',
hcaes(y = growth,
x = month,
group = sim)) %>%
hc_title(text = "51 Simulations") %>%
hc_xAxis(title = list(text = "months")) %>%
hc_yAxis(title = list(text = "dollar growth"),
labels = list(format = "${value}")) %>%
hc_add_theme(hc_theme_flat()) %>%
hc_exporting(enabled = TRUE) %>%
hc_legend(enabled = FALSE)</code></pre>
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<p>We just plotted 51 lines in <code>highcharter</code> using a tidy <code>tibble</code>. For tidy data fans out there, this is a big deal because we can stay in the grammar of the tidyverse but also use <code>highcharter</code>.</p>
<p>Very similar to what we did with <code>ggplot</code>, let’s isolate the maximum, minimum and median simulations and save them to an object called <code>mc_max_med_min</code>.</p>
<pre class="r"><code>mc_max_med_min <-
mc_gathered %>%
filter(
last(growth) == sim_summary$max ||
last(growth) == sim_summary$median ||
last(growth) == sim_summary$min) %>%
group_by(sim)</code></pre>
<p>Now we pass that filtered object to <code>hchart()</code>.</p>
<pre class="r"><code>hchart(mc_max_med_min,
type = 'line',
hcaes(y = growth,
x = month,
group = sim)) %>%
hc_title(text = "Min, Max, Median Simulations") %>%
hc_xAxis(title = list(text = "months")) %>%
hc_yAxis(title = list(text = "dollar growth"),
labels = list(format = "${value}")) %>%
hc_add_theme(hc_theme_flat()) %>%
hc_exporting(enabled = TRUE) %>%
hc_legend(enabled = FALSE)</code></pre>
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<p>That concludes our visualization of Monte Carlo simulations.</p>
<script>window.location.href='https://rviews.rstudio.com/2018/06/13/monte-carlo-part-two/';</script>
Monte Carlo
https://rviews.rstudio.com/2018/06/05/monte-carlo/
Tue, 05 Jun 2018 00:00:00 +0000https://rviews.rstudio.com/2018/06/05/monte-carlo/
<p>Today, we change gears from our previous work on <a href="https://rviews.rstudio.com/2018/05/10/rolling-fama-french/">Fama French</a> and run a Monte Carlo (MC) simulation of future portfolio returns. Monte Carlo relies on repeated, random sampling. We will sample based on two parameters: mean and standard deviation of portfolio returns. Our long-term goal (long-term == over the next two or three blog posts) is to build a Shiny app that allows an end user to build a custom portfolio, simulate returns and visualize the results. If you just can’t wait, a link to that final Shiny app is <a href="http://www.reproduciblefinance.com/shiny/monte-carlo-simulation/">here</a>.</p>
<div class="figure">
<img src="/post/2018-06-07-Monte-Carlo_files/MC.png" />
</div>
<p>Let’s get to it.</p>
<p>Devoted readers won’t be surprised that we will be simulating the returns of our usual portfolio, which consists of:</p>
<pre><code>+ SPY (S&P 500 fund) weighted 25%
+ EFA (a non-US equities fund) weighted 25%
+ IJS (a small-cap value fund) weighted 20%
+ EEM (an emerging-mkts fund) weighted 20%
+ AGG (a bond fund) weighted 10%</code></pre>
<p>Before we can simulate that portfolio, we need to calculate portfolio monthly returns, which was covered in my previous post, <a href="https://rviews.rstudio.com/2017/10/11/from-asset-to-portfolio-returns/">Introduction to Portfolio Returns</a>.</p>
<p>I won’t go through the logic again, but the code is here:</p>
<pre class="r"><code>library(tidyquant)
library(tidyverse)
library(timetk)
library(broom)
symbols <- c("SPY","EFA", "IJS", "EEM","AGG")
prices <-
getSymbols(symbols, src = 'yahoo',
from = "2012-12-31",
to = "2017-12-31",
auto.assign = TRUE, warnings = FALSE) %>%
map(~Ad(get(.))) %>%
reduce(merge) %>%
`colnames<-`(symbols)
w <- c(0.25, 0.25, 0.20, 0.20, 0.10)
asset_returns_long <-
prices %>%
to.monthly(indexAt = "lastof", OHLC = FALSE) %>%
tk_tbl(preserve_index = TRUE, rename_index = "date") %>%
gather(asset, returns, -date) %>%
group_by(asset) %>%
mutate(returns = (log(returns) - log(lag(returns)))) %>%
na.omit()
portfolio_returns_tq_rebalanced_monthly <-
asset_returns_long %>%
tq_portfolio(assets_col = asset,
returns_col = returns,
weights = w,
col_rename = "returns",
rebalance_on = "months")</code></pre>
<p>We will be working with the data object <code>portfolio_returns_tq_rebalanced_monthly</code> and we first find the mean and <a href="http://www.reproduciblefinance.com/code/standard-deviation/">standard deviation</a> of returns.</p>
<p>We will name those variables <code>mean_port_return</code> and <code>stddev_port_return</code>.</p>
<pre class="r"><code>mean_port_return <-
mean(portfolio_returns_tq_rebalanced_monthly$returns)
stddev_port_return <-
sd(portfolio_returns_tq_rebalanced_monthly$returns)</code></pre>
<p>Then we use the <code>rnorm()</code> function to sample from a distribution with mean equal to <code>mean_port_return</code> and standard deviation equal to <code>stddev_port_return</code>. That is the crucial random sampling that underpins this exercise.</p>
<p>We also must decide how many draws to pull from this distribution, meaning how many monthly returns we will simulate. 120 months is 10 years, and that feels like a good amount of time.</p>
<pre class="r"><code>simulated_monthly_returns <- rnorm(120,
mean_port_return,
stddev_port_return)</code></pre>
<p>Have a quick look at the simulated monthly returns.</p>
<pre class="r"><code>head(simulated_monthly_returns)</code></pre>
<pre><code>[1] 0.05216143 0.02271485 -0.04271307 0.04811250 -0.05575058 0.06006096</code></pre>
<pre class="r"><code>tail(simulated_monthly_returns)</code></pre>
<pre><code>[1] 0.024794729 0.008539198 -0.018852629 -0.002656127 -0.025583337
[6] 0.004412755</code></pre>
<p>Next, we calculate how a dollar would have grown given those random monthly returns. We first add a 1 to each of our monthly returns, because we start with $1.</p>
<pre class="r"><code>simulated_returns_add_1 <-
tibble(c(1, 1 + simulated_monthly_returns)) %>%
`colnames<-`("returns")
head(simulated_returns_add_1)</code></pre>
<pre><code># A tibble: 6 x 1
returns
<dbl>
1 1
2 1.05
3 1.02
4 0.957
5 1.05
6 0.944</code></pre>
<p>That data is now ready to be converted into the cumulative growth of a dollar. We can use either <code>accumulate()</code> from <code>purrr</code> or <code>cumprod()</code>. Let’s use both of them with <code>mutate()</code> and confirm consistent, reasonable results.</p>
<pre class="r"><code>simulated_growth <-
simulated_returns_add_1 %>%
mutate(growth1 = accumulate(returns, function(x, y) x * y),
growth2 = accumulate(returns, `*`),
growth3 = cumprod(returns)) %>%
select(-returns)
tail(simulated_growth)</code></pre>
<pre><code># A tibble: 6 x 3
growth1 growth2 growth3
<dbl> <dbl> <dbl>
1 2.09 2.09 2.09
2 2.11 2.11 2.11
3 2.07 2.07 2.07
4 2.06 2.06 2.06
5 2.01 2.01 2.01
6 2.02 2.02 2.02</code></pre>
<p>We just ran three simulations of dollar growth over 120 months. We passed in the same monthly returns, and that’s why we got three equivalent results.</p>
<p>Are they reasonable? What compound annual growth rate (CAGR) is implied by this simulation?</p>
<pre class="r"><code>cagr <-
((simulated_growth$growth1[nrow(simulated_growth)]^
(1/10)) - 1) * 100
cagr <- round(cagr, 2)</code></pre>
<p>This simulation implies an annual compounded growth of 7.26%. That seems reasonable given our actual returns have all been taken from a raging bull market. Remember, the above code is a simulation based on sampling from a normal distribution. If you re-run this code on your own, you will get a different result.</p>
<p>If we feel good about this first simulation, we can run several more to get a sense for how they are distributed. Before we do that, let’s create several different functions that could run the same simulation.</p>
<div id="several-simulation-functions" class="section level2">
<h2>Several Simulation Functions</h2>
<p>Let’s build three simulation functions that incorporate the <code>accumulate()</code> and <code>cumprod()</code> workflows above. We have confirmed they give consistent results so it’s a matter of stylistic preference as to which one is chosen in the end. Perhaps you feel that one is more flexible or extensible, or fits better with your team’s code flows.</p>
<p>Each of the below functions needs four arguments: N for the number of months to simulate (we chose 120 above), <code>init_value</code> for the starting value (we used $1 above), and the mean-standard deviation pair to create draws from a normal distribution. We <em>choose</em> N and <code>init_value</code>, and derive the mean-standard deviation pair from our portfolio monthly returns.</p>
<p>Here is our first growth simulation function using <code>accumulate()</code>.</p>
<pre class="r"><code>simulation_accum_1 <- function(init_value, N, mean, stdev) {
tibble(c(init_value, 1 + rnorm(N, mean, stdev))) %>%
`colnames<-`("returns") %>%
mutate(growth =
accumulate(returns,
function(x, y) x * y)) %>%
select(growth)
}</code></pre>
<p>Almost identical, here is the second simulation function using <code>accumulate()</code>.</p>
<pre class="r"><code>simulation_accum_2 <- function(init_value, N, mean, stdev) {
tibble(c(init_value, 1 + rnorm(N, mean, stdev))) %>%
`colnames<-`("returns") %>%
mutate(growth = accumulate(returns, `*`)) %>%
select(growth)
}</code></pre>
<p>Finally, here is a simulation function using <code>cumprod()</code>.</p>
<pre class="r"><code>simulation_cumprod <- function(init_value, N, mean, stdev) {
tibble(c(init_value, 1 + rnorm(N, mean, stdev))) %>%
`colnames<-`("returns") %>%
mutate(growth = cumprod(returns)) %>%
select(growth)
}</code></pre>
<p>Here is a function that uses all three methods, in case we want a fast way to re-confirm consistency.</p>
<pre class="r"><code>simulation_confirm_all <- function(init_value, N, mean, stdev) {
tibble(c(init_value, 1 + rnorm(N, mean, stdev))) %>%
`colnames<-`("returns") %>%
mutate(growth1 = accumulate(returns, function(x, y) x * y),
growth2 = accumulate(returns, `*`),
growth3 = cumprod(returns)) %>%
select(-returns)
}</code></pre>
<p>Let’s test that <code>confirm_all()</code> function with an <code>init_value</code> of 1, N of 120, and our parameters.</p>
<pre class="r"><code>simulation_confirm_all_test <-
simulation_confirm_all(1, 120,
mean_port_return, stddev_port_return)
tail(simulation_confirm_all_test)</code></pre>
<pre><code># A tibble: 6 x 3
growth1 growth2 growth3
<dbl> <dbl> <dbl>
1 2.26 2.26 2.26
2 2.22 2.22 2.22
3 2.17 2.17 2.17
4 2.21 2.21 2.21
5 2.20 2.20 2.20
6 2.23 2.23 2.23</code></pre>
<p>That’s all for today. Next time, we will explore methods for running more than one simulation with the above functions and then visualizing the results. See you then.</p>
</div>
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Exploring R Packages with cranly
https://rviews.rstudio.com/2018/05/31/exploring-r-packages/
Thu, 31 May 2018 00:00:00 +0000https://rviews.rstudio.com/2018/05/31/exploring-r-packages/
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<p>In a <a href="https://rviews.rstudio.com/2018/03/08/cran-package-metadata/">previous post</a>, I showed a very simple example of using the R function <code>tools::CRAN_package_db()</code> to analyze information about CRAN packages. <code>CRAN_package_db()</code> extracts the metadata CRAN stores on all of its 12,000 plus packages and arranges it into a “database”, actually a complicated data frame in which some columns have vectors or lists as entries.</p>
<p>It’s simple to run the function and it doesn’t take very long on my Mac Book Air.</p>
<pre class="r"><code>p_db <- tools::CRAN_package_db()</code></pre>
<p>The following gives some insight into what’s contained in the data frame.</p>
<pre class="r"><code>dim(p_db)</code></pre>
<pre><code>## [1] 12635 65</code></pre>
<pre class="r"><code>matrix(names(p_db),ncol=2)</code></pre>
<pre><code>## [,1] [,2]
## [1,] "Package" "Collate.windows"
## [2,] "Version" "Contact"
## [3,] "Priority" "Copyright"
## [4,] "Depends" "Date"
## [5,] "Imports" "Description"
## [6,] "LinkingTo" "Encoding"
## [7,] "Suggests" "KeepSource"
## [8,] "Enhances" "Language"
## [9,] "License" "LazyData"
## [10,] "License_is_FOSS" "LazyDataCompression"
## [11,] "License_restricts_use" "LazyLoad"
## [12,] "OS_type" "MailingList"
## [13,] "Archs" "Maintainer"
## [14,] "MD5sum" "Note"
## [15,] "NeedsCompilation" "Packaged"
## [16,] "Additional_repositories" "RdMacros"
## [17,] "Author" "SysDataCompression"
## [18,] "Authors@R" "SystemRequirements"
## [19,] "Biarch" "Title"
## [20,] "BugReports" "Type"
## [21,] "BuildKeepEmpty" "URL"
## [22,] "BuildManual" "VignetteBuilder"
## [23,] "BuildResaveData" "ZipData"
## [24,] "BuildVignettes" "Published"
## [25,] "Built" "Path"
## [26,] "ByteCompile" "X-CRAN-Comment"
## [27,] "Classification/ACM" "Reverse depends"
## [28,] "Classification/ACM-2012" "Reverse imports"
## [29,] "Classification/JEL" "Reverse linking to"
## [30,] "Classification/MSC" "Reverse suggests"
## [31,] "Classification/MSC-2010" "Reverse enhances"
## [32,] "Collate" "MD5sum"
## [33,] "Collate.unix" "Package"</code></pre>
<p>Looking at a few rows and columns gives a feel for how complicated its structure is.</p>
<pre class="r"><code>p_db[1:10, c(1,2,4,5)]</code></pre>
<pre><code>## Package Version Depends
## 1 A3 1.0.0 R (>= 2.15.0), xtable, pbapply
## 2 abbyyR 0.5.4 R (>= 3.2.0)
## 3 abc 2.1 R (>= 2.10), abc.data, nnet, quantreg, MASS, locfit
## 4 abc.data 1.0 R (>= 2.10)
## 5 ABC.RAP 0.9.0 R (>= 3.1.0)
## 6 ABCanalysis 1.2.1 R (>= 2.10)
## 7 abcdeFBA 0.4 Rglpk,rgl,corrplot,lattice,R (>= 2.10)
## 8 ABCoptim 0.15.0 <NA>
## 9 ABCp2 1.2 MASS
## 10 abcrf 1.7 R(>= 3.1)
## Imports
## 1 <NA>
## 2 httr, XML, curl, readr, plyr, progress
## 3 <NA>
## 4 <NA>
## 5 graphics, stats, utils
## 6 plotrix
## 7 <NA>
## 8 Rcpp, graphics, stats, utils
## 9 <NA>
## 10 readr, MASS, matrixStats, ranger, parallel, stringr, Rcpp (>=\n0.11.2)</code></pre>
<p>So, having spent a little time leaning how vexing working with this data can be, I was delighted when I discovered Ioannis Kosmidis’ <code>cranly</code> package during my March “Top 40” review. <code>cranly</code> is a very impressive package, built along tidy principles, that is helpful for learning about individual packages, analyzing the structure of package and author relationships, and searching for packages.</p>
<pre class="r"><code>library(cranly)
library(tidyverse)</code></pre>
<pre><code>## ── Attaching packages ──────────────────────────────────────────────────── tidyverse 1.2.1 ──</code></pre>
<pre><code>## ✔ ggplot2 2.2.1 ✔ purrr 0.2.4
## ✔ tibble 1.4.2 ✔ dplyr 0.7.5
## ✔ tidyr 0.8.1 ✔ stringr 1.3.1
## ✔ readr 1.1.1 ✔ forcats 0.3.0</code></pre>
<pre><code>## ── Conflicts ─────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()</code></pre>
<p>The first really impressive feature is a “one button” clean function that does an amazing job of getting the data in shape to work with. In my preliminary work, I struggled just to get the author data clean. In the approach that I took, getting rid of text like [aut, cre] to get a count of authors took more regular expression work than I wanted to deal with. But <code>clean_CRAN_db</code> does a good job of cleaning up the whole database. Note that the helper function <code>clean_up_author</code> has a considerable number of hard-coded text strings that must have taken hours to get right.</p>
<pre class="r"><code>package_db <- clean_CRAN_db(p_db)</code></pre>
<p>Once you have the clean data, it is easy to run some pretty interesting analyses. This first example, straight out of the package vignette, builds the network of package relationships based on which packages import which, and then plots a summary for the top 20 most imported packages.</p>
<pre class="r"><code>package_network <- build_network(package_db)
package_summaries <- summary(package_network)
plot(package_summaries, according_to = "n_imported_by", top = 20)</code></pre>
<p><img src="/post/2018-05-30-exploring-r-packages_files/figure-html/unnamed-chunk-6-1.png" width="672" /></p>
<p>There is also a built-in function to compute the importance or relevance of a package using the <a href="http://www.math.cornell.edu/~mec/Winter2009/RalucaRemus/Lecture3/lecture3.html">page rank</a> algorithm.</p>
<pre class="r"><code>plot(package_summaries, according_to = "page_rank", top = 20)</code></pre>
<p><img src="/post/2018-05-30-exploring-r-packages_files/figure-html/unnamed-chunk-7-1.png" width="672" /></p>
<p>The <code>build_network</code> function also offers the opportunity to investigate the collaboration of package authors by building a network from the authors’ perspective.</p>
<pre class="r"><code>author_network <- build_network(object = package_db, perspective = "author")</code></pre>
<p>Here, we look at J.J. Allaire’s network. <code>exact = FALSE</code> means that the algorithm is not using exact matching.</p>
<pre class="r"><code>plot(author_network, author = "JJ Allaire", exact = FALSE)</code></pre>
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Seonghyun","Kirill Muller","Luciano Selzer","Matthew Lincoln","Maximilian Held","Michael Sachs","Peter Hickey","Sahir Bhatnagar","Steve Simpson","Vincent Fulco","Zhuoer Dong","Bartek Szopka","jQuery Foundation","FriendCode Inc","R Foundation","Duncan Murdoch","Jeffrey Horner","David Robinson","Google Inc","Michael Friendly","Mango Solutions","Johannes Ranke","Mike Bostock","Wush Wu","Ruben Arslan","Carl Boettiger","Noam Ross","Kaiyin Zhong","John MacFarlane","Ramnath Vaidyanathan","Taiyun Wei","Robert Krzyzanowski","Carson Sievert","Joe Cheng","Mark Otto","Jacob Thornton","Bootstrap","Twitter Inc","Brian Reavis","Kristopher Michael Kowal","Denis Ineshin","Sami Samhuri","Jonathan Keane","Erin LeDell","Joshua Kunst","Jonathan Sidi","Kenton Russell","Michael Chirico","Ryan Hafen","Frank E Harrell Jr","Nathan Russell","Nacho Caballero","Qiang Kou","Maximilian Girlich","SpryMedia","Leon Gersen","Dan Vanderkam","Jonathan Owen","Petr Shevtsov","Ben Baumer","Julien Barnier","Google","Barbara Borges","Keen IO","Abdullah Almsaeed","Jonas Mosbech","Noel Bossart","Lea Verou","Dmitry Baranovskiy","Sencha Labs","Bojan Djuricic","Tomas Sardyha","Steve Matteson","Microsoft","Kohske Takahashi","Brian Diggs","Alex Zvoleff","Joseph Larmarange","Kamil Slowikowski","Kevin Kuo","H2O ai","Navdeep Gill","Sebastian Meyer","Andre Simon","Qiang Li","Dave Raggett","Ivan Sagalaev","Drifty","François Chollet","Daniel Falbel","Wouter Van Der Bijl","Martin Studer","Adam Vogt","Alastair Andrew","Aron Atkins","Ashley Manton","Cassio Pereira","Donald Arseneau","Doug Hemken","Elio Campitelli","Fabian Hirschmann","Fitch Simeon","Gregoire Detrez","Heewon Jeon","Hodges Daniel","Jake Burkhead","James Manton","Jared Lander","Jason Punyon","Javier Luraschi","Jeff Arnold","Jenny Bryan","Jeremy Ashkenas","Jeremy Stephens","John Honaker","Johan Toloe","Kevin K Smith","Kirill Mueller","Martin Modrák","Michel Kuhlmann","Nick Salkowski","Obada Mahdi","Ruaridh Williamson","Scott Kostyshak","Sietse Brouwer","Simon de Bernard","Sylvain Rousseau","Thibaut Assus","Thibaut Lamadon","Tom Torsney-Weir","Trevor Davis","Viktoras Veitas","Zachary Foster","Marcus Geelnard","Ajax org B V","Zeno Rocha","Nick Payne","Julie Cameron","Quicken Loans","Mozilla","Marion Praz","Adam November","Vicent Marti","Natacha Porte","Charlotte Wickham","Association Computing Machinery","Jonathan McPherson","Jason Long","Renyuan Zou","Michael Rose","Doug Ashton","John Chambers","Gregory Vandenbrouck","Intel","Hakim El Hattab","Asvin Goel","Greg Denehy","Roy Storey","Alexander Farkas","Scott Jehl","Greg Franko","W3C","Dave Gandy","Ben Sperry","Aidan Lister","Vadim Makeev","Oleg Jahson","Slava Oliyanchuk","Roman Komarov","Artem Polikarpov","Tony Ganch","Denis Hananein","Michal Malohlava","Jakub Hava","Gary Ritchie","Journal Statistical","Elsevier","Miao Yu","Stefan Petre","Andrew Rowls","John Fraser","John Gruber","Masayuki Tanaka","Shaun Bowe","Materialize","Yuxi You","Kevin Decker","Rodrigo Fernandes","Yauheni Pakala","Dave Liepmann"],"id":["RStudio","Randall Pruim","Henrik Bengtsson","Dean Attali","Karl Forner","Michal Bojanowski","Hadley Wickham","Winston Chang","Bob Rudis","David Hugh-Jones","Yihui Xie","Weicheng Zhu","Jalal-Edine ZAWAM","Francois Guillem","Benoit Thieurmel","Titouan Robert","RTE","Jeroen Ooms","Dirk Eddelbuettel","Daniel Gromer","John Muschelli","R Core","Karl Broman","Richard Cotton","Yuan Tang","Gábor Csárdi","Jim Hester","Thomas Leeper","Apache Foundation","Oliver Keyes","Nick Golding","Rob Hyndman","Romain Francois","Bryan Lewis","Douglas Bates","Yixuan Qiu","Ben Marwick","Aaron Wolen","Beilei Bian","Forest Fang","Garrick Aden-Buie","Hiroaki Yutani","Ian Lyttle","JJ Allaire","Kevin Ushey","Leonardo Collado-Torres","Xianying Tan","RStudio Inc","Albert Kim","Alessandro Samuel-Rosa","Andrzej Oles","Bastiaan Quast","Chester Ismay","Christophe Dervieux","Clifton Franklund","Daniel Emaasit","David Shuman","Drew Tyre","Frans van Dunne","Jeff Allen","Jennifer Bryan","Jonathan McPhers","Junwen Huang","Kevin Cheung","Kim Seonghyun","Kirill Muller","Luciano Selzer","Matthew Lincoln","Maximilian Held","Michael Sachs","Peter Hickey","Sahir Bhatnagar","Steve Simpson","Vincent Fulco","Zhuoer Dong","Bartek Szopka","jQuery Foundation","FriendCode Inc","R Foundation","Duncan Murdoch","Jeffrey Horner","David Robinson","Google Inc","Michael Friendly","Mango Solutions","Johannes Ranke","Mike Bostock","Wush Wu","Ruben Arslan","Carl Boettiger","Noam Ross","Kaiyin Zhong","John MacFarlane","Ramnath Vaidyanathan","Taiyun Wei","Robert Krzyzanowski","Carson Sievert","Joe Cheng","Mark Otto","Jacob Thornton","Bootstrap","Twitter Inc","Brian Reavis","Kristopher Michael Kowal","Denis Ineshin","Sami Samhuri","Jonathan Keane","Erin LeDell","Joshua Kunst","Jonathan Sidi","Kenton Russell","Michael Chirico","Ryan Hafen","Frank E Harrell Jr","Nathan Russell","Nacho Caballero","Qiang Kou","Maximilian Girlich","SpryMedia","Leon Gersen","Dan Vanderkam","Jonathan Owen","Petr Shevtsov","Ben Baumer","Julien Barnier","Google","Barbara Borges","Keen IO","Abdullah Almsaeed","Jonas Mosbech","Noel Bossart","Lea Verou","Dmitry Baranovskiy","Sencha Labs","Bojan Djuricic","Tomas Sardyha","Steve Matteson","Microsoft","Kohske Takahashi","Brian Diggs","Alex Zvoleff","Joseph Larmarange","Kamil Slowikowski","Kevin Kuo","H2O ai","Navdeep Gill","Sebastian Meyer","Andre Simon","Qiang Li","Dave Raggett","Ivan Sagalaev","Drifty","François Chollet","Daniel Falbel","Wouter Van Der Bijl","Martin Studer","Adam Vogt","Alastair Andrew","Aron Atkins","Ashley Manton","Cassio Pereira","Donald Arseneau","Doug Hemken","Elio Campitelli","Fabian Hirschmann","Fitch Simeon","Gregoire Detrez","Heewon Jeon","Hodges Daniel","Jake Burkhead","James Manton","Jared Lander","Jason Punyon","Javier Luraschi","Jeff Arnold","Jenny Bryan","Jeremy Ashkenas","Jeremy Stephens","John Honaker","Johan Toloe","Kevin K Smith","Kirill Mueller","Martin Modrák","Michel Kuhlmann","Nick Salkowski","Obada Mahdi","Ruaridh Williamson","Scott Kostyshak","Sietse Brouwer","Simon de Bernard","Sylvain Rousseau","Thibaut Assus","Thibaut Lamadon","Tom Torsney-Weir","Trevor Davis","Viktoras Veitas","Zachary Foster","Marcus Geelnard","Ajax org B V","Zeno Rocha","Nick Payne","Julie Cameron","Quicken Loans","Mozilla","Marion Praz","Adam November","Vicent Marti","Natacha Porte","Charlotte Wickham","Association Computing Machinery","Jonathan McPherson","Jason Long","Renyuan Zou","Michael Rose","Doug Ashton","John Chambers","Gregory Vandenbrouck","Intel","Hakim El Hattab","Asvin Goel","Greg Denehy","Roy Storey","Alexander Farkas","Scott Jehl","Greg Franko","W3C","Dave Gandy","Ben Sperry","Aidan Lister","Vadim Makeev","Oleg Jahson","Slava Oliyanchuk","Roman Komarov","Artem Polikarpov","Tony Ganch","Denis Hananein","Michal Malohlava","Jakub Hava","Gary Ritchie","Journal Statistical","Elsevier","Miao Yu","Stefan Petre","Andrew Rowls","John Fraser","John Gruber","Masayuki Tanaka","Shaun Bowe","Materialize","Yuxi You","Kevin Decker","Rodrigo Fernandes","Yauheni Pakala","Dave Liepmann"],"title":["Author: RStudio<br>446 collaborators in 103 packages: <br>ABC.RAP, AmesHousing, analogsea, babynames<br>bigrquery, bindr, bindrcpp, blob<br>callr, cowplot, crosstalk, curl<br>DBItest, dbplyr, devtools, dplyr<br>dtplyr, dygraphs, feather, flexdashboard<br>fontquiver, forcats, fs, gdtools<br>ggplot2, ggplot2movies, ggridges, ggstance<br>ggvis, googledrive, googleway, haven<br>htmlwidgets, httr, JuniperKernel, keras<br>keyring, knitrProgressBar, later, lazyeval<br>leaflet, manipulate, markdown, miniUI<br>modelr, nycflights13, odbc, pillar<br>pixels, pkgdown, pool, processx<br>profvis, promises, purrr, purrrlyr<br>r2d3, rappdirs, RcppParallel, readr<br>readxl, recipes, remotes, reticulate<br>revealjs, rlang, RLumShiny, RMariaDB<br>rmdshower, RMySQL, roxygen2, RPostgres<br>rsample, rsparkling, RSQLite, rstudioapi<br>rticles, rvest, scales, shiny<br>shinybootstrap2, shinydashboard, shinythemes, sparklyr<br>stringr, svglite, swagger, tensorflow<br>testthat, tfdatasets, tfestimators, tfruns<br>tibble, tidyposterior, tidyr, tidyselect<br>tidyverse, tidyxl, usethis, vdiffr<br>withr, xml2, yardstick","Author: Randall Pruim<br>46 collaborators in 13 packages: <br>abd, fastR, fastR2, ggformula<br>Lock5withR, mosaic, mosaicCalc, mosaicCore<br>mosaicData, NHANES, rticles, Sleuth2<br>Sleuth3","Author: Henrik Bengtsson<br>198 collaborators in 38 packages: <br>ACNE, aroma.affymetrix, aroma.apd, aroma.cn<br>aroma.core, BatchJobs, BrailleR, calmate<br>covr, dChipIO, digest, doFuture<br>future, future.apply, future.BatchJobs, future.batchtools<br>future.callr, globals, googleComputeEngineR, knitr<br>listenv, markdown, matrixStats, profmem<br>PSCBS, R.cache, R.devices, R.filesets<br>R.huge, R.matlab, R.methodsS3, R.oo<br>R.rsp, R.utils, RJaCGH, RPushbullet<br>startup, sudoku","Author: Dean Attali<br>45 collaborators in 11 packages: <br>addinslist, bookdown, colourpicker, ddpcr<br>ezknitr, ggExtra, ggquickeda, lightsout<br>shinyalert, shinyjs, timevis","Author: Karl Forner<br>111 collaborators in 5 packages: <br>allelic, BayesFactor, covr, knitr<br>RcppProgress","Author: Michal Bojanowski<br>125 collaborators in 6 packages: <br>alluvial, bookdown, intergraph, knitr<br>lspline, oai","Author: Hadley Wickham<br>710 collaborators in 123 packages: <br>analogsea, assertthat, babynames, bigQueryR<br>bigrquery, blob, bnclassify, bookdown<br>broom, cellranger, classifly, cli<br>clusterfly, colorplaner, curl, damr<br>DBI, dbplyr, DescribeDisplay, DescTools<br>devtools, dplyr, dtplyr, evaluate<br>fda, feather, forcats, fs<br>fueleconomy, gdtools, geozoo, GGally<br>ggmap, ggmosaic, ggplot2, ggplot2movies<br>ggstance, ggthemes, ggvis, gh<br>gtable, haven, hflights, HistData<br>httr, itertools, knitr, knitrProgressBar<br>labelled, lazyeval, leaflet, lemon<br>lubridate, lvplot, magrittr, meifly<br>memoise, modelr, namespace, nasaweather<br>nlmixr, nullabor, nycflights13, odbc<br>packagedocs, partools, pillar, pkgdown<br>plotrix, plumbr, plyr, prettydoc<br>productplots, profr, proto, pryr<br>purrr, purrrlyr, rappdirs, Rd2roxygen<br>readr, readxl, recipes, remotes<br>reshape, reshape2, rggobi, rlang<br>RMariaDB, rmarkdown, RMySQL, roxygen2<br>RPostgres, rsample, RSQLite, rstan<br>rstudioapi, rticles, rvest, RxODE<br>scales, sessioninfo, sf, skimr<br>spectacles, stringr, svglite, testthat<br>tibble, tidyr, tidyselect, tidyverse<br>tidyxl, tourr, tourrGui, tribe<br>unjoin, usethis, wesanderson, withr<br>xml2, yaml, yesno","Author: Winston Chang<br>172 collaborators in 33 packages: <br>analogsea, bisectr, callr, colorplaner<br>devtools, downloader, EcoGenetics, extrafont<br>extrafontdb, fontcm, gcookbook, ggplot2<br>ggstance, ggvis, googleComputeEngineR, httpuv<br>lemon, namespace, processx, profvis<br>R6, remotes, rmarkdown, Rttf2pt1<br>sessioninfo, shiny, shinybootstrap2, shinydashboard<br>shinytest, shinythemes, webdriver, webshot<br>withr","Author: Bob Rudis<br>135 collaborators in 41 packages: <br>analogsea, cdcfluview, censys, cymruservices<br>darksky, docxtractr, epidata, flexdashboard<br>gdns, geoparser, ggalt, ggthemes<br>GSODR, hrbrthemes, htmltidy, hyphenatr<br>iptools, longurl, metricsgraphics, ndjson<br>osmdata, qrencoder, rgeolocate, rvg<br>securitytxt, sergeant, slackr, spiderbar<br>splashr, statebins, swatches, SWMPrExtension<br>tigris, uaparserjs, urltools, vegalite<br>viridis, viridisLite, voteogram, waffle<br>wand","Author: David Hugh-Jones<br>106 collaborators in 5 packages: <br>anim.plots, covr, huxtable, knitr<br>refset","Author: Yihui Xie<br>389 collaborators in 40 packages: <br>animation, blogdown, bookdown, BrailleR<br>citr, corrplot, DT, evaluate<br>formatR, fun, highr, htmlwidgets<br>imguR, installr, kableExtra, knitr<br>leaflet, markdown, mime, MSG<br>params, prettydoc, printr, R2SWF<br>Rd2roxygen, rhandsontable, rmarkdown, rticles<br>servr, shiny, testit, threejs<br>tikzDevice, tinytex, tufte, webshot<br>widgetframe, xaringan, xfun, yaml","Author: Weicheng Zhu<br>94 collaborators in 5 packages: <br>animation, AssocTests, edcc, knitr<br>PedCNV","Author: Jalal-Edine ZAWAM<br>24 collaborators in 6 packages: <br>antaresProcessing, antaresRead, antaresViz, leaflet.minicharts<br>manipulateWidget, spMaps","Author: Francois Guillem<br>26 collaborators in 8 packages: <br>antaresProcessing, antaresRead, antaresViz, leaflet.minicharts<br>leafletR, manipulateWidget, tinyProject, webshot","Author: Benoit Thieurmel<br>36 collaborators in 10 packages: <br>antaresProcessing, antaresRead, antaresViz, dygraphs<br>manipulateWidget, rAmCharts, ROI.plugin.clp, spMaps<br>suncalc, visNetwork","Author: Titouan Robert<br>26 collaborators in 6 packages: <br>antaresProcessing, antaresRead, antaresViz, manipulateWidget<br>rAmCharts, visNetwork","Author: RTE<br>24 collaborators in 6 packages: <br>antaresProcessing, antaresRead, antaresViz, leaflet.minicharts<br>manipulateWidget, spMaps","Author: Jeroen Ooms<br>139 collaborators in 59 packages: <br>antiword, base64, bcrypt, brotli<br>cld2, cld3, codemetar, commonmark<br>covr, curl, gdtools, geojson<br>gpg, graphql, httpuv, hunspell<br>ijtiff, jose, jqr, js<br>jsonld, jsonlite, magick, markdown<br>minimist, Mobilize, mongolite, monkeylearn<br>Ohmage, opencpu, openssl, pdftools<br>protolite, RAppArmor, redland, rgdal<br>rjade, RMariaDB, RMySQL, RPostgres<br>RProtoBuf, RPublica, rsvg, rversions<br>rzmq, s2, sf, sodium<br>spelling, sys, tesseract, unix<br>unrtf, V8, webp, webutils<br>writexl, xml2, xslt","Author: Dirk Eddelbuettel<br>332 collaborators in 72 packages: <br>anytime, AsioHeaders, BH, bigFastlm<br>DescTools, digest, drat, fortunes<br>gaussfacts, gcbd, gettz, gtrendsR<br>gunsales, hurricaneexposure, inline, komaletter<br>lbfgs, linl, littler, mvabund<br>mvst, n1qn1, nanotime, nlmixr<br>nloptr, permGPU, pinp, pkgKitten<br>prrd, random, RApiDatetime, RApiSerialize<br>Rblpapi, Rcpp, RcppAnnoy, RcppAPT<br>RcppArmadillo, RcppBDT, RcppBlaze, RcppCCTZ<br>RcppClassic, RcppClassicExamples, RcppCNPy, RcppDE<br>RcppEigen, RcppExamples, RcppFaddeeva, RcppGetconf<br>RcppGSL, RcppMsgPack, RcppQuantuccia, RcppRedis<br>RcppSMC, RcppStreams, RcppTOML, RcppXts<br>RcppZiggurat, RDieHarder, reticulate, rfoaas<br>RInside, Rmalschains, rmsfact, RPostgreSQL<br>RProtoBuf, RPushbullet, RQuantLib, RVowpalWabbit<br>sanitizers, tensorflow, tint, x13binary","Author: Daniel Gromer<br>7 collaborators in 2 packages: <br>apa, dygraphs","Author: John Muschelli<br>102 collaborators in 29 packages: <br>ari, brainR, cifti, crsra<br>diffr, fedreporter, freesurfer, fslr<br>gcite, gifti, glassdoor, kirby21.base<br>kirby21.fmri, kirby21.t1, knitr, matlabr<br>neurobase, neurohcp, nitrcbot, oasis<br>oro.nifti, papayar, rscopus, spant<br>spm12r, stapler, sublime, tuber<br>WhiteStripe","Author: R Core<br>456 collaborators in 79 packages: <br>ARTP2, bbmle, BinQuasi, BNN<br>BoutrosLab.plotting.general, car, caret, CHNOSZ<br>CholWishart, chron, condvis, date<br>dendextend, devtools, dgof, dispRity<br>distr, distrMod, DtD, dynamichazard<br>effects, EMCluster, expint, fansi<br>flashClust, forecast, foreign, future.apply<br>gap.datasets, gdtools, GLDEX, GLDreg<br>glmBfp, icd, inlinedocs, lrmest<br>Matrix, MCMCpack, metaplus, mixlm<br>multimode, namespace, nlme, nscancor<br>nsprcomp, pbdDMAT, pbdMPI, pbdZMQ<br>PCICt, permute, ph2hetero, phia<br>properties, pryr, pubh, QuasiSeq<br>RandomFields, RApiDatetime, RApiSerialize, readr<br>readstata13, remoter, RobAStBase, robets<br>rstan, rstanarm, RxODE, sciplot<br>sem, sessioninfo, shiny, SpatialExtremes<br>statip, stringdist, surveillance, testthat<br>vetr, weights, wikipediatrend","Author: Karl Broman<br>43 collaborators in 6 packages: <br>aRxiv, BatchMap, cowsay, onemap<br>qtlDesign, rticles","Author: Richard Cotton<br>118 collaborators in 33 packages: <br>assertive, assertive.base, assertive.code, assertive.data<br>assertive.data.uk, assertive.data.us, assertive.datetimes, assertive.files<br>assertive.matrices, assertive.models, assertive.numbers, assertive.properties<br>assertive.reflection, assertive.sets, assertive.strings, assertive.types<br>DYM, flippant, knitr, listless<br>multipanelfigure, pathological, poio, rebus<br>rebus.base, rebus.datetimes, rebus.numbers, rebus.unicode<br>runittotestthat, setter, sig, spatialkernel<br>withr","Author: Yuan Tang<br>91 collaborators in 14 packages: <br>autoplotly, caret, dml, forecast<br>ggfortify, h2o4gpu, keras, lfda<br>onnx, reticulate, tensorflow, tfdatasets<br>tfestimators, xgboost","Author: Gábor Csárdi<br>63 collaborators in 40 packages: <br>available, callr, cli, clisymbols<br>cranlike, crayon, debugme, desc<br>disposables, dotenv, filelock, gh<br>keypress, keyring, liteq, parsedate<br>pingr, pkgconfig, prettycode, processx<br>progress, rematch2, remotes, rhub<br>rmdshower, rstack, rversions, sand<br>sankey, secret, sessioninfo, shinytest<br>shinytoastr, showimage, spark, sys<br>webdriver, whoami, xmlparsedata, zip","Author: Jim Hester<br>194 collaborators in 25 packages: <br>available, bench, covr, desc<br>devtools, digest, fs, glue<br>gmailr, knitr, knitrBootstrap, lintr<br>markdown, memoise, naniar, odbc<br>pacman, primerTree, readr, remotes<br>repr, rex, spelling, types<br>withr","Author: Thomas Leeper<br>166 collaborators in 13 packages: <br>aws.alexa, batman, cowsay, drat<br>essurvey, installr, knitr, MarginalMediation<br>markdown, monkeylearn, poio, sparktex<br>UNF","Author: Apache Foundation<br>86 collaborators in 14 packages: <br>base64url, commonsMath, lexicon, openNLPdata<br>PortfolioEffectHFT, Rdroolsjars, ReporteRsjars, rkafkajars<br>RKEAjars, rtika, sparklyr, XLConnect<br>XLConnectJars, xlsxjars","Author: Oliver Keyes<br>80 collaborators in 36 packages: <br>batman, birdnik, dotwhisker, exif<br>favnums, forwards, geohash, hail<br>humaniformat, iptools, lucr, muckrock<br>olctools, openssl, ores, osi<br>pageviews, phonics, piton, primes<br>rdian, reconstructr, rEDM, rgeolocate<br>rLTP, rticles, rwars, threewords<br>triebeard, udapi, urltools, webreadr<br>whoapi, wicket, WikidataR, WikipediR","Author: Nick Golding<br>16 collaborators in 9 packages: <br>BayesComm, default, GRaF, greta<br>malariaAtlas, pop, tensorflow, versions<br>zoon","Author: Rob Hyndman<br>77 collaborators in 12 packages: <br>bfast, eechidna, forecast, fpp2<br>hdrcde, hts, Mcomp, rmarkdown<br>robets, sugrrants, thief, tsibble","Author: Romain Francois<br>268 collaborators in 28 packages: <br>bibtex, bigFastlm, DescTools, highlight<br>inline, knitr, knitrProgressBar, mvst<br>operators, permGPU, Rcpp, Rcpp11<br>RcppArmadillo, RcppBDT, RcppBlaze, RcppClassic<br>RcppClassicExamples, RcppEigen, RcppExamples, RcppGSL<br>RcppParallel, readr, RInside, RProtoBuf<br>sos, svMisc, svTools, tibble","Author: Bryan Lewis<br>41 collaborators in 4 packages: <br>bigalgebra, digest, flexdashboard, reticulate","Author: Douglas Bates<br>115 collaborators in 25 packages: <br>bigFastlm, car, coda, cond<br>Devore7, EngrExpt, hoa, lme4<br>marg, Matrix, MatrixModels, MEMSS<br>minqa, mlmRev, mvnmle, NISTnls<br>nlme, nlreg, pedigreemm, PKPDmodels<br>Rcpp, RcppBlaze, RcppEigen, rstanarm<br>SASmixed","Author: Yixuan Qiu<br>113 collaborators in 20 packages: <br>bigFastlm, bookdown, fun, gdtools<br>highr, markdown, oem, prettydoc<br>R2SWF, rARPACK, rationalfun, RcppEigen<br>RcppNumerical, recosystem, RSpectra, showtext<br>showtextdb, svglite, sysfonts, vennLasso","Author: Ben Marwick<br>86 collaborators in 8 packages: <br>binford, bookdown, cvequality, drake<br>eechidna, ggalt, gsloid, rticles","Author: Aaron Wolen<br>102 collaborators in 5 packages: <br>biolink, knitr, komaletter, linl<br>qtl","Author: Beilei Bian<br>14 collaborators in 2 packages: <br>blogdown, radmixture","Author: Forest Fang<br>99 collaborators in 3 packages: <br>blogdown, knitr, shinyAce","Author: Garrick Aden-Buie<br>101 collaborators in 3 packages: <br>blogdown, knitr, xaringan","Author: Hiroaki Yutani<br>100 collaborators in 9 packages: <br>blogdown, datadogr, estatapi, gghighlight<br>githubinstall, knitr, kntnr, kokudosuuchi<br>qiitr","Author: Ian Lyttle<br>109 collaborators in 6 packages: <br>blogdown, boxr, bsplus, knitr<br>lubridate, vembedr","Author: JJ Allaire<br>375 collaborators in 33 packages: <br>blogdown, bookdown, config, DT<br>dygraphs, flexdashboard, htmlwidgets, keras<br>knitr, learnr, manipulate, manipulateWidget<br>markdown, packrat, prettydoc, r2d3<br>Rcpp, RcppParallel, reticulate, revealjs<br>rmarkdown, rmdshower, rsconnect, rsparkling<br>rstudioapi, rticles, shiny, sparklyr<br>tensorflow, tfdatasets, tfestimators, tfruns<br>tufte","Author: Kevin Ushey<br>241 collaborators in 20 packages: <br>blogdown, bookdown, cronR, DescTools<br>icd, packrat, Rcpp, Rcpp11<br>RcppParallel, RcppRoll, reticulate, rex<br>rmarkdown, rsnps, rstudioapi, sourcetools<br>sparklyr, tfdatasets, tfestimators, withr","Author: Leonardo Collado-Torres<br>10 collaborators in 1 packages: <br>blogdown","Author: Xianying Tan<br>19 collaborators in 2 packages: <br>blogdown, DT","Author: RStudio Inc<br>126 collaborators in 12 packages: <br>blogdown, bookdown, config, d3heatmap<br>DT, htmltools, learnr, qrage<br>rmarkdown, skimr, tinytex, tufte","Author: Albert Kim<br>47 collaborators in 2 packages: <br>bookdown, infer","Author: Alessandro Samuel-Rosa<br>60 collaborators in 4 packages: <br>bookdown, febr, pedometrics, spsann","Author: Andrzej Oles<br>57 collaborators in 3 packages: <br>bookdown, markdown, tufte","Author: Bastiaan Quast<br>68 collaborators in 11 packages: <br>bookdown, decompr, diagonals, gvc<br>learNN, rddapp, rddtools, rnn<br>rticles, sigmoid, wiod","Author: Chester Ismay<br>61 collaborators in 4 packages: <br>bookdown, fivethirtyeight, infer, moderndive","Author: Christophe Dervieux<br>125 collaborators in 3 packages: <br>bookdown, knitr, nomisr","Author: Clifton Franklund<br>38 collaborators in 1 packages: <br>bookdown","Author: Daniel Emaasit<br>38 collaborators in 1 packages: <br>bookdown","Author: David Shuman<br>38 collaborators in 1 packages: <br>bookdown","Author: Drew Tyre<br>38 collaborators in 1 packages: <br>bookdown","Author: Frans van Dunne<br>38 collaborators in 1 packages: <br>bookdown","Author: Jeff Allen<br>97 collaborators in 6 packages: <br>bookdown, plumber, rhandsontable, rmarkdown<br>shinyAce, shinyTree","Author: Jennifer Bryan<br>69 collaborators in 15 packages: <br>bookdown, cellranger, clipr, gapminder<br>gh, googleAuthR, googledrive, googlesheets<br>rdfp, readxl, reprex, repurrrsive<br>salesforcer, searchConsoleR, usethis","Author: Jonathan McPhers<br>38 collaborators in 1 packages: <br>bookdown","Author: Junwen Huang<br>38 collaborators in 2 packages: <br>bookdown, somebm","Author: Kevin Cheung<br>38 collaborators in 1 packages: <br>bookdown","Author: Kim Seonghyun<br>38 collaborators in 4 packages: <br>bookdown, cbar, refnr, tropr","Author: Kirill Muller<br>41 collaborators in 2 packages: <br>bookdown, qdapTools","Author: Luciano Selzer<br>64 collaborators in 4 packages: <br>bookdown, broom, ggfortify, multcompView","Author: Matthew Lincoln<br>58 collaborators in 6 packages: <br>bookdown, broom, clipr, europop<br>fuzzr, hypothesisr","Author: Maximilian Held<br>39 collaborators in 2 packages: <br>bookdown, qmethod","Author: Michael Sachs<br>41 collaborators in 3 packages: <br>bookdown, cosinor, ggquickeda","Author: Peter Hickey<br>45 collaborators in 2 packages: <br>bookdown, matrixStats","Author: Sahir Bhatnagar<br>41 collaborators in 3 packages: <br>bookdown, casebase, manhattanly","Author: Steve Simpson<br>41 collaborators in 3 packages: <br>bookdown, clipr, googleformr","Author: Vincent Fulco<br>38 collaborators in 1 packages: <br>bookdown","Author: Zhuoer Dong<br>47 collaborators in 2 packages: <br>bookdown, yaml","Author: Bartek Szopka<br>47 collaborators in 2 packages: <br>bookdown, DT","Author: jQuery Foundation<br>197 collaborators in 17 packages: <br>bookdown, crosstalk, dygraphs, ggvis<br>lazyrmd, leaflet, metricsgraphics, profvis<br>QCA, qrage, qtlcharts, rhandsontable<br>rmarkdown, shiny, sparkline, tfruns<br>vdiffr","Author: FriendCode Inc<br>38 collaborators in 1 packages: <br>bookdown","Author: R Foundation<br>70 collaborators in 9 packages: <br>BoutrosLab.plotting.general, dispRity, expint, MCMCpack<br>multimode, ph2hetero, rticles, statip<br>xml2","Author: Duncan Murdoch<br>262 collaborators in 22 packages: <br>BrailleR, car, digest, ellipse<br>fortunes, gpclib, gsl, inline<br>knitr, manipulateWidget, nlsr, orientlib<br>patchDVI, Rcmdr, Rdpack, rgl<br>rglwidget, sciplot, spatialkernel, tables<br>tkrgl, vcdExtra","Author: Jeffrey Horner<br>64 collaborators in 15 packages: <br>brew, Cairo, datamap, FastRWeb<br>markdown, mime, network, networkDynamic<br>PResiduals, redcapAPI, RMariaDB, RMySQL<br>Rook, TimeWarp, yaml","Author: David Robinson<br>138 collaborators in 12 packages: <br>broom, dataCompareR, fuzzyjoin, gutenbergr<br>knitr, orcutt, reprex, rgeolocate<br>tidygenomics, tidytext, unvotes, widyr","Author: Google Inc<br>94 collaborators in 15 packages: <br>brotli, cld3, deepboost, odbc<br>PortfolioEffectHFT, Rdroolsjars, re2r, rmarkdown<br>s2, snappier, sparsepp, tensorflow<br>tfdatasets, tfestimators, timechange","Author: Michael Friendly<br>383 collaborators in 24 packages: <br>ca, candisc, car, DescTools<br>effects, fortunes, genridge, Guerry<br>heplots, HistData, installr, knitr<br>Lahman, logmult, maptools, matlib<br>mvinfluence, sem, statquotes, tableplot<br>vcd, vcdExtra, vegan, WordPools","Author: Mango Solutions<br>29 collaborators in 6 packages: <br>callr, mangoTraining, processx, remotes<br>rmdshower, sasMap","Author: Johannes Ranke<br>94 collaborators in 7 packages: <br>chemCal, drfit, kinfit, knitr<br>mkin, rlo, webchem","Author: Mike Bostock<br>81 collaborators in 15 packages: <br>ChemoSpec, collapsibleTree, D3partitionR, d3r<br>edgebundleR, exCon, ggiraph, ggvis<br>leaflet.extras, profvis, r2d3, scatterD3<br>sunburstR, tfruns, vegalite","Author: Wush Wu<br>117 collaborators in 9 packages: <br>ckanr, digest, FeatureHashing, knitr<br>Rcereal, RcppCNPy, supc, swirl<br>swirlify","Author: Ruben Arslan<br>30 collaborators in 2 packages: <br>codebook, rmarkdown","Author: Carl Boettiger<br>86 collaborators in 19 packages: <br>codemetar, dataone, drat, EcoNetGen<br>EML, knitcitations, pmc, rcrossref<br>rdflib, rdryad, redland, rfigshare<br>rfishbase, rfisheries, RNeXML, rplos<br>rticles, taxize, treebase","Author: Noam Ross<br>128 collaborators in 9 packages: <br>codemetar, cowsay, data.tree, fasterize<br>knitr, opencage, randgeo, viridis<br>viridisLite","Author: Kaiyin Zhong<br>87 collaborators in 3 packages: <br>CollapsABEL, collUtils, knitr","Author: John MacFarlane<br>31 collaborators in 2 packages: <br>commonmark, rmarkdown","Author: Ramnath Vaidyanathan<br>118 collaborators in 7 packages: <br>concaveman, gistr, htmlwidgets, knitr<br>rticles, servr, sparkline","Author: Taiyun Wei<br>92 collaborators in 3 packages: <br>corrplot, fun, knitr","Author: Robert Krzyzanowski<br>109 collaborators in 4 packages: <br>covr, knitr, recombinator, rex","Author: Carson Sievert<br>61 collaborators in 10 packages: <br>cowsay, eechidna, etl, flexdashboard<br>LDAvis, pitchRx, plotly, repr<br>servr, XML2R","Author: Joe Cheng<br>245 collaborators in 18 packages: <br>crosstalk, d3heatmap, DT, flexdashboard<br>googleVis, htmlwidgets, httpuv, knitr<br>later, leaflet, markdown, miniUI<br>packrat, promises, raster, rmarkdown<br>santaR, shiny","Author: Mark Otto<br>97 collaborators in 5 packages: <br>crosstalk, rmarkdown, shiny, shinybootstrap2<br>shinyWidgets","Author: Jacob Thornton<br>97 collaborators in 5 packages: <br>crosstalk, rmarkdown, shiny, shinybootstrap2<br>shinyWidgets","Author: Bootstrap<br>97 collaborators in 5 packages: <br>crosstalk, rmarkdown, shiny, shinybootstrap2<br>shinyWidgets","Author: Twitter Inc<br>97 collaborators in 5 packages: <br>crosstalk, rmarkdown, shiny, shinybootstrap2<br>shinyWidgets","Author: Brian Reavis<br>51 collaborators in 4 packages: <br>crosstalk, DT, shiny, shinybootstrap2","Author: Kristopher Michael Kowal<br>34 collaborators in 2 packages: <br>crosstalk, shiny","Author: Denis Ineshin<br>34 collaborators in 2 packages: <br>crosstalk, shiny","Author: Sami Samhuri<br>34 collaborators in 2 packages: <br>crosstalk, shiny","Author: Jonathan Keane<br>87 collaborators in 2 packages: <br>crunch, knitr","Author: Erin LeDell<br>19 collaborators in 7 packages: <br>cvAUC, h2o4gpu, Metrics, rHealthDataGov<br>rsparkling, subsemble, SuperLearner","Author: Joshua Kunst<br>33 collaborators in 5 packages: <br>d3plus, flexdashboard, ggthemes, highcharter<br>rchess","Author: Jonathan Sidi<br>91 collaborators in 10 packages: <br>d3Tree, ggedit, heatmaply, jsTree<br>knitr, lmmen, regexSelect, shinyHeatmaply<br>slickR, texPreview","Author: Kenton Russell<br>65 collaborators in 11 packages: <br>d3Tree, formattable, htmltidy, htmlwidgets<br>leaflet, mapedit, mapview, networkD3<br>rbokeh, rmapshaper, rpivotTable","Author: Michael Chirico<br>94 collaborators in 4 packages: <br>data.table, funchir, knitr, vcov","Author: Ryan Hafen<br>36 collaborators in 11 packages: <br>datadr, flexdashboard, geofacet, geogrid<br>gqlr, housingData, lazyrmd, packagedocs<br>rbokeh, stlplus, trelliscope","Author: Frank E Harrell Jr<br>186 collaborators in 5 packages: <br>DescTools, greport, Hmisc, knitr<br>rms","Author: Nathan Russell<br>107 collaborators in 3 packages: <br>DescTools, hashmap, Rcpp","Author: Nacho Caballero<br>100 collaborators in 3 packages: <br>df2json, knitr, markdown","Author: Qiang Kou<br>26 collaborators in 5 packages: <br>digest, MultiCNVDetect, Rcpp, RcppDL<br>RcppMLPACK","Author: Maximilian Girlich<br>9 collaborators in 1 packages: <br>DT","Author: SpryMedia<br>41 collaborators in 3 packages: <br>DT, shiny, shinybootstrap2","Author: Leon Gersen<br>34 collaborators in 2 packages: <br>DT, shinyWidgets","Author: Dan Vanderkam<br>7 collaborators in 1 packages: <br>dygraphs","Author: Jonathan Owen<br>38 collaborators in 4 packages: <br>dygraphs, networkD3, rbokeh, rhandsontable","Author: Petr Shevtsov<br>7 collaborators in 1 packages: <br>dygraphs","Author: Ben Baumer<br>100 collaborators in 6 packages: <br>etl, infer, knitr, mdsr<br>nyctaxi, teamcolors","Author: Julien Barnier<br>91 collaborators in 5 packages: <br>explor, knitr, questionr, rmdformats<br>scatterD3","Author: Google<br>31 collaborators in 5 packages: <br>feather, hrbrthemes, keras, landscapetools<br>RClickhouse","Author: Barbara Borges<br>26 collaborators in 3 packages: <br>flexdashboard, learnr, pool","Author: Keen IO<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Abdullah Almsaeed<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Jonas Mosbech<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Noel Bossart<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Lea Verou<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Dmitry Baranovskiy<br>23 collaborators in 2 packages: <br>flexdashboard, QCA","Author: Sencha Labs<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Bojan Djuricic<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Tomas Sardyha<br>17 collaborators in 1 packages: <br>flexdashboard","Author: Steve Matteson<br>11 collaborators in 2 packages: <br>fontLiberation, prettydoc","Author: Microsoft<br>10 collaborators in 3 packages: <br>foreach, glmnetUtils, RcppParallel","Author: Kohske Takahashi<br>104 collaborators in 5 packages: <br>formatR, ggpolypath, knitr, labeledLoop<br>markdown","Author: Brian Diggs<br>147 collaborators in 2 packages: <br>fortunes, knitr","Author: Alex Zvoleff<br>85 collaborators in 5 packages: <br>gfcanalysis, glcm, knitr, wrspathrow<br>wrspathrowData","Author: Joseph Larmarange<br>108 collaborators in 6 packages: <br>GGally, knitr, labelled, lubridate<br>prevR, questionr","Author: Kamil Slowikowski<br>95 collaborators in 3 packages: <br>ggpmisc, ggrepel, knitr","Author: Kevin Kuo<br>20 collaborators in 5 packages: <br>graphframes, mleap, networkD3, sparklyr<br>tfestimators","Author: H2O ai<br>10 collaborators in 3 packages: <br>h2o, h2o4gpu, rsparkling","Author: Navdeep Gill<br>9 collaborators in 2 packages: <br>h2o4gpu, rsparkling","Author: Sebastian Meyer<br>105 collaborators in 4 packages: <br>hhh4contacts, knitr, polyCub, surveillance","Author: Andre Simon<br>86 collaborators in 2 packages: <br>highlight, knitr","Author: Qiang Li<br>88 collaborators in 2 packages: <br>highr, knitr","Author: Dave Raggett<br>37 collaborators in 2 packages: <br>htmltidy, rmarkdown","Author: Ivan Sagalaev<br>77 collaborators in 5 packages: <br>htmltidy, profvis, rmarkdown, shiny<br>tfruns","Author: Drifty<br>31 collaborators in 2 packages: <br>ionicons, rmarkdown","Author: François Chollet<br>7 collaborators in 1 packages: <br>keras","Author: Daniel Falbel<br>13 collaborators in 5 packages: <br>keras, ptstem, ptwikiwords, rslp<br>tfestimators","Author: Wouter Van Der Bijl<br>7 collaborators in 1 packages: <br>keras","Author: Martin Studer<br>13 collaborators in 3 packages: <br>keras, XLConnect, XLConnectJars","Author: Adam Vogt<br>85 collaborators in 1 packages: <br>knitr","Author: Alastair Andrew<br>85 collaborators in 1 packages: <br>knitr","Author: Aron Atkins<br>119 collaborators in 3 packages: <br>knitr, packrat, rmarkdown","Author: Ashley Manton<br>85 collaborators in 1 packages: <br>knitr","Author: Cassio Pereira<br>85 collaborators in 1 packages: <br>knitr","Author: Donald Arseneau<br>85 collaborators in 1 packages: <br>knitr","Author: Doug Hemken<br>85 collaborators in 2 packages: <br>knitr, SASmarkdown","Author: Elio Campitelli<br>85 collaborators in 1 packages: <br>knitr","Author: Fabian Hirschmann<br>85 collaborators in 1 packages: <br>knitr","Author: Fitch Simeon<br>85 collaborators in 1 packages: <br>knitr","Author: Gregoire Detrez<br>85 collaborators in 1 packages: <br>knitr","Author: Heewon Jeon<br>86 collaborators in 4 packages: <br>knitr, KoNLP, Ruchardet, Sejong","Author: Hodges Daniel<br>85 collaborators in 1 packages: <br>knitr","Author: Jake Burkhead<br>85 collaborators in 1 packages: <br>knitr","Author: James Manton<br>89 collaborators in 5 packages: <br>knitr, morgenstemning, nat, nat.nblast<br>nat.templatebrains","Author: Jared Lander<br>85 collaborators in 2 packages: <br>knitr, resumer","Author: Jason Punyon<br>85 collaborators in 1 packages: <br>knitr","Author: Javier Luraschi<br>131 collaborators in 8 packages: <br>knitr, pixels, profvis, r2d3<br>rmarkdown, sparklyr, sparkwarc, swagger","Author: Jeff Arnold<br>85 collaborators in 1 packages: <br>knitr","Author: Jenny Bryan<br>89 collaborators in 2 packages: <br>knitr, tidyxl","Author: Jeremy Ashkenas<br>85 collaborators in 1 packages: <br>knitr","Author: Jeremy Stephens<br>99 collaborators in 3 packages: <br>knitr, redcapAPI, yaml","Author: John Honaker<br>85 collaborators in 1 packages: <br>knitr","Author: Johan Toloe<br>85 collaborators in 1 packages: <br>knitr","Author: Kevin K Smith<br>85 collaborators in 1 packages: <br>knitr","Author: Kirill Mueller<br>113 collaborators in 3 packages: <br>knitr, ProjectTemplate, rticles","Author: Martin Modrák<br>85 collaborators in 1 packages: <br>knitr","Author: Michel Kuhlmann<br>85 collaborators in 1 packages: <br>knitr","Author: Nick Salkowski<br>85 collaborators in 1 packages: <br>knitr","Author: Obada Mahdi<br>85 collaborators in 1 packages: <br>knitr","Author: Ruaridh Williamson<br>93 collaborators in 2 packages: <br>knitr, rio","Author: Scott Kostyshak<br>85 collaborators in 1 packages: <br>knitr","Author: Sietse Brouwer<br>85 collaborators in 1 packages: <br>knitr","Author: Simon de Bernard<br>85 collaborators in 1 packages: <br>knitr","Author: Sylvain Rousseau<br>85 collaborators in 1 packages: <br>knitr","Author: Thibaut Assus<br>85 collaborators in 1 packages: <br>knitr","Author: Thibaut Lamadon<br>85 collaborators in 1 packages: <br>knitr","Author: Tom Torsney-Weir<br>85 collaborators in 1 packages: <br>knitr","Author: Trevor Davis<br>93 collaborators in 2 packages: <br>knitr, rappdirs","Author: Viktoras Veitas<br>85 collaborators in 1 packages: <br>knitr","Author: Zachary Foster<br>104 collaborators in 5 packages: <br>knitr, metacoder, taxa, taxize<br>traits","Author: Marcus Geelnard<br>16 collaborators in 3 packages: <br>later, RcppParallel, reticulate","Author: Ajax org B V<br>12 collaborators in 2 packages: <br>learnr, shinyAce","Author: Zeno Rocha<br>8 collaborators in 1 packages: <br>learnr","Author: Nick Payne<br>8 collaborators in 1 packages: <br>learnr","Author: Julie Cameron<br>8 collaborators in 1 packages: <br>learnr","Author: Quicken Loans<br>8 collaborators in 1 packages: <br>learnr","Author: Mozilla<br>12 collaborators in 2 packages: <br>learnr, metricsgraphics","Author: Marion Praz<br>7 collaborators in 1 packages: <br>manipulateWidget","Author: Adam November<br>15 collaborators in 1 packages: <br>markdown","Author: Vicent Marti<br>15 collaborators in 1 packages: <br>markdown","Author: Natacha Porte<br>15 collaborators in 1 packages: <br>markdown","Author: Charlotte Wickham<br>18 collaborators in 3 packages: <br>munsell, repurrrsive, rticles","Author: Association Computing Machinery<br>44 collaborators in 2 packages: <br>OpenMx, rticles","Author: Jonathan McPherson<br>58 collaborators in 3 packages: <br>packrat, rmarkdown, shiny","Author: Jason Long<br>7 collaborators in 1 packages: <br>prettydoc","Author: Renyuan Zou<br>7 collaborators in 1 packages: <br>prettydoc","Author: Michael Rose<br>7 collaborators in 1 packages: <br>prettydoc","Author: Doug Ashton<br>15 collaborators in 2 packages: <br>radarchart, rmdshower","Author: John Chambers<br>9 collaborators in 2 packages: <br>Rcpp, Rcpp11","Author: Gregory Vandenbrouck<br>7 collaborators in 1 packages: <br>RcppParallel","Author: Intel<br>7 collaborators in 1 packages: <br>RcppParallel","Author: Hakim El Hattab<br>4 collaborators in 1 packages: <br>revealjs","Author: Asvin Goel<br>4 collaborators in 1 packages: <br>revealjs","Author: Greg Denehy<br>4 collaborators in 1 packages: <br>revealjs","Author: Roy Storey<br>30 collaborators in 1 packages: <br>rmarkdown","Author: Alexander Farkas<br>54 collaborators in 2 packages: <br>rmarkdown, shiny","Author: Scott Jehl<br>54 collaborators in 2 packages: <br>rmarkdown, shiny","Author: Greg Franko<br>30 collaborators in 1 packages: <br>rmarkdown","Author: W3C<br>30 collaborators in 1 packages: <br>rmarkdown","Author: Dave Gandy<br>55 collaborators in 3 packages: <br>rmarkdown, shiny, waffle","Author: Ben Sperry<br>30 collaborators in 1 packages: <br>rmarkdown","Author: Aidan Lister<br>30 collaborators in 1 packages: <br>rmarkdown","Author: Vadim Makeev<br>11 collaborators in 1 packages: <br>rmdshower","Author: Oleg Jahson<br>11 collaborators in 1 packages: <br>rmdshower","Author: Slava Oliyanchuk<br>11 collaborators in 1 packages: <br>rmdshower","Author: Roman Komarov<br>11 collaborators in 1 packages: <br>rmdshower","Author: Artem Polikarpov<br>11 collaborators in 1 packages: <br>rmdshower","Author: Tony Ganch<br>11 collaborators in 1 packages: <br>rmdshower","Author: Denis Hananein<br>11 collaborators in 1 packages: <br>rmdshower","Author: Michal Malohlava<br>6 collaborators in 1 packages: <br>rsparkling","Author: Jakub Hava<br>6 collaborators in 1 packages: <br>rsparkling","Author: Gary Ritchie<br>4 collaborators in 1 packages: <br>rstudioapi","Author: Journal Statistical<br>17 collaborators in 1 packages: <br>rticles","Author: Elsevier<br>17 collaborators in 1 packages: <br>rticles","Author: Miao Yu<br>17 collaborators in 1 packages: <br>rticles","Author: Stefan Petre<br>24 collaborators in 1 packages: <br>shiny","Author: Andrew Rowls<br>24 collaborators in 1 packages: <br>shiny","Author: John Fraser<br>24 collaborators in 1 packages: <br>shiny","Author: John Gruber<br>24 collaborators in 1 packages: <br>shiny","Author: Masayuki Tanaka<br>11 collaborators in 1 packages: <br>tfruns","Author: Shaun Bowe<br>11 collaborators in 1 packages: <br>tfruns","Author: Materialize<br>11 collaborators in 1 packages: <br>tfruns","Author: Yuxi You<br>11 collaborators in 1 packages: <br>tfruns","Author: Kevin Decker<br>11 collaborators in 1 packages: <br>tfruns","Author: Rodrigo Fernandes<br>11 collaborators in 1 packages: <br>tfruns","Author: Yauheni Pakala<br>11 collaborators in 1 packages: <br>tfruns","Author: Dave Liepmann<br>4 collaborators in 1 packages: <br>tufte"]},"edges":{"from":["Yihui Xie","Beilei Bian","Forest Fang","Garrick Aden-Buie","Hiroaki Yutani","Ian Lyttle","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","Yihui Xie","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ Allaire","JJ 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<p>It is also possible to study individual packages. Here, I plot the very simple dependency tree for the time series package <code>xts</code>. There is a very good argument to be made that the simpler the dependency tree the more stable and reliable the package.</p>
<pre class="r"><code>xts_tree <- build_dependence_tree(package_network, "xts")
plot(xts_tree)</code></pre>
<div id="htmlwidget-2" style="width:672px;height:480px;" class="visNetwork html-widget"></div>
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<p>As a final example, consider how the <code>package_with()</code> function might be used to search for Bayesian packages by searching for packages with “Bayes” or “MCMC” in the description. I don’t believe that this exhausts the possibilities of <code>cranly</code>, but it should be clear that the package is a very useful tool for looking into the mysteries of CRAN.</p>
<pre class="r"><code>Bayesian_packages <- package_with(package_network, name = c("Bayes", "MCMC"))
plot(package_network, package = Bayesian_packages, legend=FALSE)</code></pre>
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href=https://CRAN.R-project.org/package=abind>abind<\/a> (1.4-5)<br>Maintainer: Tony Plate <tplate@acm.org><br>imports/imported by:2/106<br>depends/is dependency of:0/30<br>suggests/suggested by:0/20<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/abind?color=969696>","<a href=https://CRAN.R-project.org/package=acebayes>acebayes<\/a> (1.4.1)<br>Maintainer: Antony M. Overstall <A.M.Overstall@soton.ac.uk><br>imports/imported by:3/0<br>depends/is dependency of:1/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/acebayes?color=969696>","<a href=https://CRAN.R-project.org/package=adaptMCMC>adaptMCMC<\/a> (1.3)<br>Maintainer: Andreas Scheidegger <andreas.scheidegger@eawag.ch><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/adaptMCMC?color=969696>","<a href=https://CRAN.R-project.org/package=adaptsmoFMRI>adaptsmoFMRI<\/a> (1.1)<br>Maintainer: Max Hughes <hughesgm@me.com><br>imports/imported by:0/0<br>depends/is dependency of:6/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/adaptsmoFMRI?color=969696>","<a href=https://CRAN.R-project.org/package=adlift>adlift<\/a> (1.3-3)<br>Maintainer: Matt Nunes <m.nunes@lancaster.ac.uk><br>imports/imported by:0/0<br>depends/is dependency of:1/5<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/adlift?color=969696>","<a href=https://CRAN.R-project.org/package=agridat>agridat<\/a> (1.13)<br>Maintainer: Kevin Wright <kw.stat@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:46/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/agridat?color=969696>","<a href=https://CRAN.R-project.org/package=airGR>airGR<\/a> (1.0.9.64)<br>Maintainer: Olivier Delaigue <airGR@irstea.fr><br>imports/imported by:0/0<br>depends/is dependency of:0/1<br>suggests/suggested by:8/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/airGR?color=969696>","<a href=https://CRAN.R-project.org/package=akima>akima<\/a> (0.6-2)<br>Maintainer: Albrecht Gebhardt <albrecht.gebhardt@aau.at><br>imports/imported by:1/2<br>depends/is dependency of:0/0<br>suggests/suggested by:0/36<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/akima?color=969696>","<a href=https://CRAN.R-project.org/package=anominate>anominate<\/a> (0.6)<br>Maintainer: Christopher Hare <cdhare@ucdavis.edu><br>imports/imported by:0/0<br>depends/is dependency of:5/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/anominate?color=969696>","<a href=https://CRAN.R-project.org/package=ape>ape<\/a> (5.1)<br>Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr><br>imports/imported by:9/95<br>depends/is dependency of:0/81<br>suggests/suggested by:3/38<br>enhances/enhaced by:0/1<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/ape?color=969696>","<a href=https://CRAN.R-project.org/package=arm>arm<\/a> (1.10-1)<br>Maintainer: Yu-Sung Su <suyusung@tsinghua.edu.cn><br>imports/imported by:7/16<br>depends/is dependency of:4/4<br>suggests/suggested by:0/10<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/arm?color=969696>","<a href=https://CRAN.R-project.org/package=ashr>ashr<\/a> (2.2-7)<br>Maintainer: Peter Carbonetto <pcarbo@uchicago.edu><br>imports/imported by:11/1<br>depends/is dependency of:0/0<br>suggests/suggested by:8/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/ashr?color=969696>","<a href=https://CRAN.R-project.org/package=bacr>bacr<\/a> (1.0.1)<br>Maintainer: Chi Wang <chi.wang@uky.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bacr?color=969696>","<a href=https://CRAN.R-project.org/package=bamlss>bamlss<\/a> (1.0-0)<br>Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at><br>imports/imported by:8/0<br>depends/is dependency of:3/0<br>suggests/suggested by:20/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bamlss?color=969696>","<a href=https://CRAN.R-project.org/package=bang>bang<\/a> (1.0.0)<br>Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:4/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bang?color=969696>","<a href=https://CRAN.R-project.org/package=bartMachine>bartMachine<\/a> (1.2.4.2)<br>Maintainer: Adam Kapelner <kapelner@qc.cuny.edu><br>imports/imported by:3/3<br>depends/is dependency of:5/0<br>suggests/suggested by:0/4<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bartMachine?color=969696>","<a href=https://CRAN.R-project.org/package=bayesAB>bayesAB<\/a> (1.1.0)<br>Maintainer: Frank Portman <frank1214@gmail.com><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:5/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesAB?color=969696>","<a href=https://CRAN.R-project.org/package=bayesammi>bayesammi<\/a> (0.1.0)<br>Maintainer: Muhammad Yaseen <myaseen208@gmail.com><br>imports/imported by:13/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesammi?color=969696>","<a href=https://CRAN.R-project.org/package=BayesBD>BayesBD<\/a> (1.2)<br>Maintainer: Nicholas Syring <nasyrin@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesBD?color=969696>","<a href=https://CRAN.R-project.org/package=BayesBinMix>BayesBinMix<\/a> (1.4.1)<br>Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesBinMix?color=969696>","<a href=https://CRAN.R-project.org/package=bayesbio>bayesbio<\/a> (1.0.0)<br>Maintainer: Andrew McKenzie <amckenz@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesbio?color=969696>","<a href=https://CRAN.R-project.org/package=bayesboot>bayesboot<\/a> (0.2.1)<br>Maintainer: Rasmus Bååth <rasmus.baath@gmail.com><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesboot?color=969696>","<a href=https://CRAN.R-project.org/package=BayesCombo>BayesCombo<\/a> (1.0)<br>Maintainer: Stanley E. Lazic <stan.lazic@cantab.net><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesCombo?color=969696>","<a href=https://CRAN.R-project.org/package=BayesComm>BayesComm<\/a> (0.1-2)<br>Maintainer: Nick Golding\n<nick.golding.research@gmail.com><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesComm?color=969696>","<a href=https://CRAN.R-project.org/package=bayescount>bayescount<\/a> (0.9.99-5)<br>Maintainer: Matthew Denwood <md@sund.ku.dk><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayescount?color=969696>","<a href=https://CRAN.R-project.org/package=BayesCR>BayesCR<\/a> (2.1)<br>Maintainer: Aldo M. Garay <medina_garay@yahoo.com><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesCR?color=969696>","<a href=https://CRAN.R-project.org/package=BayesDA>BayesDA<\/a> (2012.04-1)<br>Maintainer: Kjetil Halvorsen <kjetil1001@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesDA?color=969696>","<a href=https://CRAN.R-project.org/package=bayesDccGarch>bayesDccGarch<\/a> (2.0)<br>Maintainer: Jose A Fiorucci <jafioruci@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesDccGarch?color=969696>","<a href=https://CRAN.R-project.org/package=BAYESDEF>BAYESDEF<\/a> (0.1.0)<br>Maintainer: Nery Sofia Huerta-Pacheco <nehuerta@uv.mx><br>imports/imported by:3/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BAYESDEF?color=969696>","<a href=https://CRAN.R-project.org/package=bayesDem>bayesDem<\/a> (2.5-1)<br>Maintainer: Hana Sevcikova <hanas@uw.edu><br>imports/imported by:2/0<br>depends/is dependency of:5/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesDem?color=969696>","<a href=https://CRAN.R-project.org/package=bayesDP>bayesDP<\/a> (1.3.1)<br>Maintainer: Shawn Balcome <sbalcome@mdic.org><br>imports/imported by:1/0<br>depends/is dependency of:3/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesDP?color=969696>","<a href=https://CRAN.R-project.org/package=BayesESS>BayesESS<\/a> (0.1.12)<br>Maintainer: Jaejoon Song <jjsong2@mdanderson.org><br>imports/imported by:4/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:3/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesESS?color=969696>","<a href=https://CRAN.R-project.org/package=BayesFactor>BayesFactor<\/a> (0.9.12-4.2)<br>Maintainer: Richard D. Morey <richarddmorey@gmail.com><br>imports/imported by:10/4<br>depends/is dependency of:2/2<br>suggests/suggested by:9/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesFactor?color=969696>","<a href=https://CRAN.R-project.org/package=BayesFM>BayesFM<\/a> (0.1.2)<br>Maintainer: Rémi Piatek <remi.piatek@econ.ku.dk><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesFM?color=969696>","<a href=https://CRAN.R-project.org/package=bayesGARCH>bayesGARCH<\/a> (2.1.3)<br>Maintainer: David Ardia <david.ardia.ch@gmail.com><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesGARCH?color=969696>","<a href=https://CRAN.R-project.org/package=bayesGDS>bayesGDS<\/a> (0.6.2)<br>Maintainer: Michael Braun <braunm@smu.edu><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:10/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesGDS?color=969696>","<a href=https://CRAN.R-project.org/package=BayesGESM>BayesGESM<\/a> (1.4)<br>Maintainer: Luz Marina Rondon <lumarp@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesGESM?color=969696>","<a href=https://CRAN.R-project.org/package=BayesGOF>BayesGOF<\/a> (4.0)<br>Maintainer: Doug Fletcher <tug25070@temple.edu><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesGOF?color=969696>","<a href=https://CRAN.R-project.org/package=BayesianAnimalTracker>BayesianAnimalTracker<\/a> (1.2)<br>Maintainer: Yang (Seagle) Liu <yang.liu@stat.ubc.ca><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesianAnimalTracker?color=969696>","<a href=https://CRAN.R-project.org/package=Bayesianbetareg>Bayesianbetareg<\/a> (1.2)<br>Maintainer: Margarita Marin <mmarinj@unal.edu.co><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Bayesianbetareg?color=969696>","<a href=https://CRAN.R-project.org/package=BayesianGLasso>BayesianGLasso<\/a> (0.2.0)<br>Maintainer: Patrick Trainor <patrick.trainor@louisville.edu><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesianGLasso?color=969696>","<a href=https://CRAN.R-project.org/package=BayesianNetwork>BayesianNetwork<\/a> (0.1.3)<br>Maintainer: Paul Govan <pgovan1@aggienetwork.com><br>imports/imported by:9/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesianNetwork?color=969696>","<a href=https://CRAN.R-project.org/package=BayesianTools>BayesianTools<\/a> (0.1.4)<br>Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de><br>imports/imported by:16/0<br>depends/is dependency of:0/0<br>suggests/suggested by:8/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesianTools?color=969696>","<a href=https://CRAN.R-project.org/package=bayesImageS>bayesImageS<\/a> (0.5-1)<br>Maintainer: Matt Moores <M.T.Moores@warwick.ac.uk><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesImageS?color=969696>","<a href=https://CRAN.R-project.org/package=BayesLCA>BayesLCA<\/a> (1.7)<br>Maintainer: Arthur White <arwhite@tcd.ie><br>imports/imported by:3/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesLCA?color=969696>","<a href=https://CRAN.R-project.org/package=bayesLife>bayesLife<\/a> (3.2-0)<br>Maintainer: Hana Sevcikova <hanas@uw.edu><br>imports/imported by:4/0<br>depends/is dependency of:1/2<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesLife?color=969696>","<a href=https://CRAN.R-project.org/package=bayeslm>bayeslm<\/a> (0.7.0)<br>Maintainer: Jingyu He <jingyu.he@chicagobooth.edu><br>imports/imported by:6/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:3/0<br><img src=https://cranlogs.r-pkg.org/badges/bayeslm?color=969696>","<a href=https://CRAN.R-project.org/package=bayesloglin>bayesloglin<\/a> (1.0.1)<br>Maintainer: Matthew Friedlander <friedla@yorku.ca><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesloglin?color=969696>","<a href=https://CRAN.R-project.org/package=bayeslongitudinal>bayeslongitudinal<\/a> (0.1.0)<br>Maintainer: Edwin Javier Castillo Carreño <edjcastilloca@unal.edu.co><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayeslongitudinal?color=969696>","<a href=https://CRAN.R-project.org/package=bayesLopod>bayesLopod<\/a> (1.0.1)<br>Maintainer: Camilo Sanin <camilosanin@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:5/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesLopod?color=969696>","<a href=https://CRAN.R-project.org/package=bayesm>bayesm<\/a> (3.1-0.1)<br>Maintainer: Peter Rossi <perossichi@gmail.com><br>imports/imported by:5/4<br>depends/is dependency of:0/4<br>suggests/suggested by:2/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesm?color=969696>","<a href=https://CRAN.R-project.org/package=BayesMAMS>BayesMAMS<\/a> (0.1)<br>Maintainer: Philip Pallmann <p.pallmann@lancaster.ac.uk><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesMAMS?color=969696>","<a href=https://CRAN.R-project.org/package=BayesMed>BayesMed<\/a> (1.0.1)<br>Maintainer: Michele B. Nuijten <m.b.nuijten@uvt.nl><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesMed?color=969696>","<a href=https://CRAN.R-project.org/package=bayesmeta>bayesmeta<\/a> (2.2)<br>Maintainer: Christian Roever <christian.roever@med.uni-goettingen.de><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesmeta?color=969696>","<a href=https://CRAN.R-project.org/package=bayesmix>bayesmix<\/a> (0.7-4)<br>Maintainer: Bettina Gruen <Bettina.Gruen@jku.at><br>imports/imported by:5/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesmix?color=969696>","<a href=https://CRAN.R-project.org/package=BayesMixSurv>BayesMixSurv<\/a> (0.9.1)<br>Maintainer: Alireza S. Mahani <alireza.s.mahani@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesMixSurv?color=969696>","<a href=https://CRAN.R-project.org/package=BayesNetBP>BayesNetBP<\/a> (1.3.0)<br>Maintainer: Han Yu <hyu9@buffalo.edu><br>imports/imported by:11/0<br>depends/is dependency of:3/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesNetBP?color=969696>","<a href=https://CRAN.R-project.org/package=BayesPieceHazSelect>BayesPieceHazSelect<\/a> (1.1.0)<br>Maintainer: Andrew Chapple <AndrewChapple21@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesPieceHazSelect?color=969696>","<a href=https://CRAN.R-project.org/package=BayesPiecewiseICAR>BayesPiecewiseICAR<\/a> (0.2.1)<br>Maintainer: Andrew Chapple <Andrew.G.Chapple@rice.edu><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesPiecewiseICAR?color=969696>","<a href=https://CRAN.R-project.org/package=bayesplot>bayesplot<\/a> (1.5.0)<br>Maintainer: Jonah Gabry <jsg2201@columbia.edu><br>imports/imported by:7/9<br>depends/is dependency of:0/1<br>suggests/suggested by:12/9<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesplot?color=969696>","<a href=https://CRAN.R-project.org/package=bayesPop>bayesPop<\/a> (6.2-4)<br>Maintainer: Hana Sevcikova <hanas@uw.edu><br>imports/imported by:13/0<br>depends/is dependency of:2/1<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesPop?color=969696>","<a href=https://CRAN.R-project.org/package=bayespref>bayespref<\/a> (1.0)<br>Maintainer: James A. Fordyce <jfordyce@utk.edu><br>imports/imported by:0/0<br>depends/is dependency of:5/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayespref?color=969696>","<a href=https://CRAN.R-project.org/package=bayesQR>bayesQR<\/a> (2.3)<br>Maintainer: Dries F. Benoit <Dries.Benoit@UGent.be><br>imports/imported by:0/1<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesQR?color=969696>","<a href=https://CRAN.R-project.org/package=BayesRS>BayesRS<\/a> (0.1.3)<br>Maintainer: Mirko Thalmann <mirkothalmann@hotmail.com><br>imports/imported by:7/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesRS?color=969696>","<a href=https://CRAN.R-project.org/package=bayess>bayess<\/a> (1.4)<br>Maintainer: Christian P. Robert <xian@ceremade.dauphine.fr><br>imports/imported by:0/0<br>depends/is dependency of:5/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayess?color=969696>","<a href=https://CRAN.R-project.org/package=BayesS5>BayesS5<\/a> (1.30)<br>Maintainer: Minsuk Shin <minsuk000@gmail.com><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesS5?color=969696>","<a href=https://CRAN.R-project.org/package=BayesSAE>BayesSAE<\/a> (1.0-2)<br>Maintainer: Chengchun Shi Developer <cshi4@ncsu.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesSAE?color=969696>","<a href=https://CRAN.R-project.org/package=BayesSingleSub>BayesSingleSub<\/a> (0.6.2)<br>Maintainer: Richard D. Morey <richarddmorey@gmail.com><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesSingleSub?color=969696>","<a href=https://CRAN.R-project.org/package=BayesSpec>BayesSpec<\/a> (0.5.3)<br>Maintainer: Andrew Ferris <andrew.ferris@sydney.edu.au><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesSpec?color=969696>","<a href=https://CRAN.R-project.org/package=BayesSummaryStatLM>BayesSummaryStatLM<\/a> (1.0-1)<br>Maintainer: Evgeny Savel'ev <savelev@vt.edu><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesSummaryStatLM?color=969696>","<a href=https://CRAN.R-project.org/package=bayesSurv>bayesSurv<\/a> (3.2)<br>Maintainer: Arnošt Komárek <arnost.komarek@mff.cuni.cz><br>imports/imported by:3/1<br>depends/is dependency of:3/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesSurv?color=969696>","<a href=https://CRAN.R-project.org/package=bayesTFR>bayesTFR<\/a> (6.1-2)<br>Maintainer: Hana Sevcikova <hanas@uw.edu><br>imports/imported by:8/0<br>depends/is dependency of:0/3<br>suggests/suggested by:9/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bayesTFR?color=969696>","<a href=https://CRAN.R-project.org/package=BayesTree>BayesTree<\/a> (0.3-1.4)<br>Maintainer: Robert McCulloch <robert.e.mcculloch@gmail.com><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesTree?color=969696>","<a href=https://CRAN.R-project.org/package=BayesTreePrior>BayesTreePrior<\/a> (1.0.1)<br>Maintainer: Alexia Jolicoeur-Martineau <alexia.jolicoeur-martineau@mail.mcgill.ca><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesTreePrior?color=969696>","<a href=https://CRAN.R-project.org/package=BayesTwin>BayesTwin<\/a> (1.0)<br>Maintainer: Inga Schwabe <bayestwin@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesTwin?color=969696>","<a href=https://CRAN.R-project.org/package=BayesVarSel>BayesVarSel<\/a> (1.8.0)<br>Maintainer: Anabel Forte <anabel.forte@uv.es><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesVarSel?color=969696>","<a href=https://CRAN.R-project.org/package=BayesX>BayesX<\/a> (0.3-0)<br>Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at><br>imports/imported by:6/2<br>depends/is dependency of:1/0<br>suggests/suggested by:4/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesX?color=969696>","<a href=https://CRAN.R-project.org/package=BayesXsrc>BayesXsrc<\/a> (3.0-1)<br>Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at><br>imports/imported by:0/1<br>depends/is dependency of:0/1<br>suggests/suggested by:1/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BayesXsrc?color=969696>","<a href=https://CRAN.R-project.org/package=BB>BB<\/a> (2014.10-1)<br>Maintainer: Paul Gilbert <pgilbert.ttv9z@ncf.ca><br>imports/imported by:2/16<br>depends/is dependency of:0/8<br>suggests/suggested by:4/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/BB?color=969696>","<a href=https://CRAN.R-project.org/package=Bergm>Bergm<\/a> (4.1.0)<br>Maintainer: Alberto Caimo <acaimo.stats@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Bergm?color=969696>","<a href=https://CRAN.R-project.org/package=betareg>betareg<\/a> (3.1-0)<br>Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org><br>imports/imported by:9/3<br>depends/is dependency of:0/4<br>suggests/suggested by:4/5<br>enhances/enhaced by:0/5<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/betareg?color=969696>","<a href=https://CRAN.R-project.org/package=BH>BH<\/a> (1.66.0-1)<br>Maintainer: Dirk Eddelbuettel <edd@debian.org><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/135<br><img src=https://cranlogs.r-pkg.org/badges/BH?color=969696>","<a href=https://CRAN.R-project.org/package=bhrcr>bhrcr<\/a> (1.0.0)<br>Maintainer: Colin B. Fogarty <cfogarty@mit.edu><br>imports/imported by:11/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bhrcr?color=969696>","<a href=https://CRAN.R-project.org/package=blavaan>blavaan<\/a> (0.3-1)<br>Maintainer: Edgar Merkle <merklee@missouri.edu><br>imports/imported by:9/1<br>depends/is dependency of:3/0<br>suggests/suggested by:5/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/blavaan?color=969696>","<a href=https://CRAN.R-project.org/package=bnlearn>bnlearn<\/a> (4.3)<br>Maintainer: Marco Scutari <marco.scutari@gmail.com><br>imports/imported by:0/7<br>depends/is dependency of:1/2<br>suggests/suggested by:8/7<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bnlearn?color=969696>","<a href=https://CRAN.R-project.org/package=Bolstad2>Bolstad2<\/a> (1.0-28)<br>Maintainer: James M. Curran <j.curran@auckland.ac.nz><br>imports/imported by:0/1<br>depends/is dependency of:0/2<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Bolstad2?color=969696>","<a href=https://CRAN.R-project.org/package=boot>boot<\/a> (1.3-20)<br>Maintainer: Brian Ripley <ripley@stats.ox.ac.uk><br>imports/imported by:0/114<br>depends/is dependency of:2/53<br>suggests/suggested by:2/61<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/boot?color=969696>","<a href=https://CRAN.R-project.org/package=breathteststan>breathteststan<\/a> (0.4.1)<br>Maintainer: Dieter Menne <dieter.menne@menne-biomed.de><br>imports/imported by:8/0<br>depends/is dependency of:0/0<br>suggests/suggested by:8/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:5/0<br><img src=https://cranlogs.r-pkg.org/badges/breathteststan?color=969696>","<a href=https://CRAN.R-project.org/package=bridgesampling>bridgesampling<\/a> (0.4-0)<br>Maintainer: Quentin F. Gronau <Quentin.F.Gronau@gmail.com><br>imports/imported by:9/2<br>depends/is dependency of:0/0<br>suggests/suggested by:11/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/bridgesampling?color=969696>","<a href=https://CRAN.R-project.org/package=brms>brms<\/a> (2.3.0)<br>Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com><br>imports/imported by:17/1<br>depends/is dependency of:3/0<br>suggests/suggested by:13/4<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/brms?color=969696>","<a href=https://CRAN.R-project.org/package=bssm>bssm<\/a> (0.1.5)<br>Maintainer: Jouni Helske <jouni.helske@iki.fi><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:9/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:5/0<br><img src=https://cranlogs.r-pkg.org/badges/bssm?color=969696>","<a href=https://CRAN.R-project.org/package=BTYDplus>BTYDplus<\/a> (1.0.1)<br>Maintainer: Michael Platzer <michael.platzer@gmail.com><br>imports/imported by:8/0<br>depends/is dependency of:0/0<br>suggests/suggested by:6/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/BTYDplus?color=969696>","<a href=https://CRAN.R-project.org/package=Cairo>Cairo<\/a> (1.5-9)<br>Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org><br>imports/imported by:2/10<br>depends/is dependency of:0/3<br>suggests/suggested by:1/18<br>enhances/enhaced by:1/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Cairo?color=969696>","<a href=https://CRAN.R-project.org/package=cancerTiming>cancerTiming<\/a> (3.1.8)<br>Maintainer: Elizabeth Purdom <epurdom@stat.berkeley.edu><br>imports/imported by:6/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/cancerTiming?color=969696>","<a href=https://CRAN.R-project.org/package=car>car<\/a> (3.0-0)<br>Maintainer: John Fox <jfox@mcmaster.ca><br>imports/imported by:14/84<br>depends/is dependency of:1/41<br>suggests/suggested by:12/71<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/car?color=969696>","<a href=https://CRAN.R-project.org/package=CARBayes>CARBayes<\/a> (5.0)<br>Maintainer: Duncan Lee <Duncan.Lee@glasgow.ac.uk><br>imports/imported by:10/0<br>depends/is dependency of:2/0<br>suggests/suggested by:9/1<br>enhances/enhaced by:0/1<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/CARBayes?color=969696>","<a href=https://CRAN.R-project.org/package=CARBayesdata>CARBayesdata<\/a> (2.0)<br>Maintainer: Duncan Lee <Duncan.Lee@glasgow.ac.uk><br>imports/imported by:2/2<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CARBayesdata?color=969696>","<a href=https://CRAN.R-project.org/package=CARBayesST>CARBayesST<\/a> (2.5.2)<br>Maintainer: Duncan Lee <Duncan.Lee@glasgow.ac.uk><br>imports/imported by:12/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/CARBayesST?color=969696>","<a href=https://CRAN.R-project.org/package=causaldrf>causaldrf<\/a> (0.3)<br>Maintainer: Douglas Galagate <galagated@gmail.com><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:12/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/causaldrf?color=969696>","<a href=https://CRAN.R-project.org/package=CFC>CFC<\/a> (1.1.0)<br>Maintainer: Alireza S. Mahani <alireza.s.mahani@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:5/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:3/0<br><img src=https://cranlogs.r-pkg.org/badges/CFC?color=969696>","<a href=https://CRAN.R-project.org/package=checkmate>checkmate<\/a> (1.8.5)<br>Maintainer: Michel Lang <michellang@gmail.com><br>imports/imported by:2/66<br>depends/is dependency of:0/8<br>suggests/suggested by:12/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/checkmate?color=969696>","<a href=https://CRAN.R-project.org/package=checkr>checkr<\/a> (0.2.0)<br>Maintainer: Joe Thorley <joe@poissonconsulting.ca><br>imports/imported by:0/2<br>depends/is dependency of:0/0<br>suggests/suggested by:9/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/checkr?color=969696>","<a href=https://CRAN.R-project.org/package=ChoiceModelR>ChoiceModelR<\/a> (1.2)<br>Maintainer: John V Colias <jcolias@decisionanalyst.com><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ChoiceModelR?color=969696>","<a href=https://CRAN.R-project.org/package=circglmbayes>circglmbayes<\/a> (1.2.3)<br>Maintainer: Kees Mulder <keestimmulder@gmail.com><br>imports/imported by:8/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:3/0<br><img src=https://cranlogs.r-pkg.org/badges/circglmbayes?color=969696>","<a href=https://CRAN.R-project.org/package=clinfun>clinfun<\/a> (1.0.15)<br>Maintainer: Venkatraman E. Seshan <seshanv@mskcc.org><br>imports/imported by:1/2<br>depends/is dependency of:2/5<br>suggests/suggested by:1/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/clinfun?color=969696>","<a href=https://CRAN.R-project.org/package=coalescentMCMC>coalescentMCMC<\/a> (0.4-1)<br>Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr><br>imports/imported by:3/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/coalescentMCMC?color=969696>","<a href=https://CRAN.R-project.org/package=coarseDataTools>coarseDataTools<\/a> (0.6-3)<br>Maintainer: Nicholas G. Reich <nick@schoolph.umass.edu><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/coarseDataTools?color=969696>","<a href=https://CRAN.R-project.org/package=coda>coda<\/a> (0.19-1)<br>Maintainer: Martyn Plummer <plummerm@iarc.fr><br>imports/imported by:1/151<br>depends/is dependency of:0/80<br>suggests/suggested by:0/41<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/coda?color=969696>","<a href=https://CRAN.R-project.org/package=CoinMinD>CoinMinD<\/a> (1.1)<br>Maintainer: Sumathi <sumathimr@yahoo.co.in><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CoinMinD?color=969696>","<a href=https://CRAN.R-project.org/package=colorspace>colorspace<\/a> (1.3-2)<br>Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org><br>imports/imported by:2/69<br>depends/is dependency of:1/15<br>suggests/suggested by:12/39<br>enhances/enhaced by:0/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/colorspace?color=969696>","<a href=https://CRAN.R-project.org/package=combinat>combinat<\/a> (0.0-8)<br>Maintainer: Vince Carey <stvjc@channing.harvard.edu><br>imports/imported by:0/27<br>depends/is dependency of:0/19<br>suggests/suggested by:0/7<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/combinat?color=969696>","<a href=https://CRAN.R-project.org/package=compare>compare<\/a> (0.2-6)<br>Maintainer: Paul Murrell <p.murrell@auckland.ac.nz><br>imports/imported by:0/5<br>depends/is dependency of:0/1<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/compare?color=969696>","<a href=https://CRAN.R-project.org/package=compiler>compiler<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/31<br>depends/is dependency of:0/13<br>suggests/suggested by:0/8<br>enhances/enhaced by:0/4<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/compiler?color=969696>","<a href=https://CRAN.R-project.org/package=compositions>compositions<\/a> (1.40-1)<br>Maintainer: K. Gerald van den Boogaart <support@boogaart.de><br>imports/imported by:0/3<br>depends/is dependency of:4/0<br>suggests/suggested by:1/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/compositions?color=969696>","<a href=https://CRAN.R-project.org/package=compute.es>compute.es<\/a> (0.2-4)<br>Maintainer: AC Del Re <acdelre@gmail.com><br>imports/imported by:0/1<br>depends/is dependency of:0/0<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/compute.es?color=969696>","<a href=https://CRAN.R-project.org/package=condir>condir<\/a> (0.1.1)<br>Maintainer: Angelos-Miltiadis Krypotos <amkrypotos@gmail.com><br>imports/imported by:8/0<br>depends/is dependency of:1/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/condir?color=969696>","<a href=https://CRAN.R-project.org/package=ConnMatTools>ConnMatTools<\/a> (0.3.3)<br>Maintainer: David M. Kaplan <dmkaplan2000@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ConnMatTools?color=969696>","<a href=https://CRAN.R-project.org/package=copCAR>copCAR<\/a> (2.0-2)<br>Maintainer: John Hughes <jphughesjr@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/copCAR?color=969696>","<a href=https://CRAN.R-project.org/package=CopulaDTA>CopulaDTA<\/a> (1.0.0)<br>Maintainer: Victoria N Nyaga <victoria.nyaga@outlook.com><br>imports/imported by:6/0<br>depends/is dependency of:1/0<br>suggests/suggested by:5/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CopulaDTA?color=969696>","<a href=https://CRAN.R-project.org/package=corpcor>corpcor<\/a> (1.6.9)<br>Maintainer: Korbinian Strimmer <strimmerlab@gmail.com><br>imports/imported by:1/51<br>depends/is dependency of:0/40<br>suggests/suggested by:0/4<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/corpcor?color=969696>","<a href=https://CRAN.R-project.org/package=CorrectedFDR>CorrectedFDR<\/a> (1.0)<br>Maintainer: Abbas Rahal <arahal@uOttawa.ca><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CorrectedFDR?color=969696>","<a href=https://CRAN.R-project.org/package=covr>covr<\/a> (3.1.0)<br>Maintainer: Jim Hester <james.f.hester@gmail.com><br>imports/imported by:8/3<br>depends/is dependency of:1/0<br>suggests/suggested by:13/512<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/covr?color=969696>","<a href=https://CRAN.R-project.org/package=CPBayes>CPBayes<\/a> (0.3.0)<br>Maintainer: Arunabha Majumdar <statgen.arunabha@gmail.com><br>imports/imported by:4/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CPBayes?color=969696>","<a href=https://CRAN.R-project.org/package=crmPack>crmPack<\/a> (0.2.7)<br>Maintainer: Daniel Sabanes Bove <sabanesd@roche.com><br>imports/imported by:10/0<br>depends/is dependency of:2/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/crmPack?color=969696>","<a href=https://CRAN.R-project.org/package=cubature>cubature<\/a> (1.3-11)<br>Maintainer: Balasubramanian Narasimhan <naras@stat.stanford.edu><br>imports/imported by:1/26<br>depends/is dependency of:0/7<br>suggests/suggested by:5/6<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/2<br><img src=https://cranlogs.r-pkg.org/badges/cubature?color=969696>","<a href=https://CRAN.R-project.org/package=cudaBayesreg>cudaBayesreg<\/a> (0.3-16)<br>Maintainer: Adelino Ferreira da Silva <afs@fct.unl.pt><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/cudaBayesreg?color=969696>","<a href=https://CRAN.R-project.org/package=cudaBayesregData>cudaBayesregData<\/a> (0.3-11)<br>Maintainer: Adelino Ferreira da Silva <afs@fct.unl.pt><br>imports/imported by:0/0<br>depends/is dependency of:0/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/cudaBayesregData?color=969696>","<a href=https://CRAN.R-project.org/package=CVThresh>CVThresh<\/a> (1.1.1)<br>Maintainer: Donghoh Kim <donghoh.kim@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/CVThresh?color=969696>","<a href=https://CRAN.R-project.org/package=dalmatian>dalmatian<\/a> (0.3.0)<br>Maintainer: Simon Bonner <sbonner6@uwo.ca><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/dalmatian?color=969696>","<a href=https://CRAN.R-project.org/package=data.table>data.table<\/a> (1.11.4)<br>Maintainer: Matt Dowle <mattjdowle@gmail.com><br>imports/imported by:1/367<br>depends/is dependency of:0/71<br>suggests/suggested by:7/59<br>enhances/enhaced by:0/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/data.table?color=969696>","<a href=https://CRAN.R-project.org/package=deldir>deldir<\/a> (0.1-15)<br>Maintainer: Rolf Turner <r.turner@auckland.ac.nz><br>imports/imported by:2/22<br>depends/is dependency of:0/6<br>suggests/suggested by:1/12<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/deldir?color=969696>","<a href=https://CRAN.R-project.org/package=denstrip>denstrip<\/a> (1.5.4)<br>Maintainer: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk><br>imports/imported by:1/2<br>depends/is dependency of:0/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:1/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/denstrip?color=969696>","<a href=https://CRAN.R-project.org/package=DEoptim>DEoptim<\/a> (2.2-4)<br>Maintainer: Katharine Mullen <mullenkate@gmail.com><br>imports/imported by:0/13<br>depends/is dependency of:1/8<br>suggests/suggested by:4/10<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/DEoptim?color=969696>","<a href=https://CRAN.R-project.org/package=dfcrm>dfcrm<\/a> (0.2-2)<br>Maintainer: Jimmy Duong <jkd2108@columbia.edu><br>imports/imported by:0/2<br>depends/is dependency of:0/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/dfcrm?color=969696>","<a href=https://CRAN.R-project.org/package=DHARMa>DHARMa<\/a> (0.1.6)<br>Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de><br>imports/imported by:14/1<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/DHARMa?color=969696>","<a href=https://CRAN.R-project.org/package=digest>digest<\/a> (0.6.15)<br>Maintainer: Dirk Eddelbuettel <edd@debian.org><br>imports/imported by:0/158<br>depends/is dependency of:0/14<br>suggests/suggested by:2/26<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/3<br><img src=https://cranlogs.r-pkg.org/badges/digest?color=969696>","<a href=https://CRAN.R-project.org/package=dirmcmc>dirmcmc<\/a> (1.3.3)<br>Maintainer: Abhirup Mallik <malli066@umn.edu><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/dirmcmc?color=969696>","<a href=https://CRAN.R-project.org/package=DMRMark>DMRMark<\/a> (1.1.1)<br>Maintainer: Linghao SHEN <sl013@ie.cuhk.edu.hk><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/DMRMark?color=969696>","<a href=https://CRAN.R-project.org/package=DOBAD>DOBAD<\/a> (1.0.6)<br>Maintainer: Charles Doss <cdoss@umn.edu><br>imports/imported by:3/0<br>depends/is dependency of:1/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/DOBAD?color=969696>","<a href=https://CRAN.R-project.org/package=doBy>doBy<\/a> (4.6-1)<br>Maintainer: Søren Højsgaard <sorenh@math.aau.dk><br>imports/imported by:5/8<br>depends/is dependency of:1/2<br>suggests/suggested by:7/5<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/doBy?color=969696>","<a href=https://CRAN.R-project.org/package=doMC>doMC<\/a> (1.3.5)<br>Maintainer: Rich Calaway <richcala@microsoft.com><br>imports/imported by:1/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/24<br>enhances/enhaced by:2/3<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/doMC?color=969696>","<a href=https://CRAN.R-project.org/package=doParallel>doParallel<\/a> (1.0.11)<br>Maintainer: Rich Calaway <richcala@microsoft.com><br>imports/imported by:0/223<br>depends/is dependency of:4/39<br>suggests/suggested by:3/67<br>enhances/enhaced by:2/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/doParallel?color=969696>","<a href=https://CRAN.R-project.org/package=dplyr>dplyr<\/a> (0.7.5)<br>Maintainer: Hadley Wickham <hadley@rstudio.com><br>imports/imported by:12/797<br>depends/is dependency of:0/53<br>suggests/suggested by:20/212<br>enhances/enhaced by:0/2<br>linkingto/linked by:4/0<br><img src=https://cranlogs.r-pkg.org/badges/dplyr?color=969696>","<a href=https://CRAN.R-project.org/package=DSBayes>DSBayes<\/a> (1.1)<br>Maintainer: Wenliang Yao <yaow080@gmail.com><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/DSBayes?color=969696>","<a href=https://CRAN.R-project.org/package=dyn>dyn<\/a> (0.2-9.6)<br>Maintainer: M. Leeds <markleeds2@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:7/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/dyn?color=969696>","<a href=https://CRAN.R-project.org/package=e1071>e1071<\/a> (1.6-8)<br>Maintainer: David Meyer <David.Meyer@R-project.org><br>imports/imported by:6/93<br>depends/is dependency of:0/22<br>suggests/suggested by:9/66<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/e1071?color=969696>","<a href=https://CRAN.R-project.org/package=EbayesThresh>EbayesThresh<\/a> (1.4-12)<br>Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com><br>imports/imported by:2/1<br>depends/is dependency of:0/4<br>suggests/suggested by:5/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/EbayesThresh?color=969696>","<a href=https://CRAN.R-project.org/package=EDMeasure>EDMeasure<\/a> (1.2.0)<br>Maintainer: Ze Jin <zj58@cornell.edu><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/EDMeasure?color=969696>","<a href=https://CRAN.R-project.org/package=effectFusion>effectFusion<\/a> (1.0)<br>Maintainer: Daniela Pauger <daniela.pauger@jku.at><br>imports/imported by:7/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/effectFusion?color=969696>","<a href=https://CRAN.R-project.org/package=EKMCMC>EKMCMC<\/a> (0.1.0)<br>Maintainer: Boseung Choi <cbskust@gmail.com><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/EKMCMC?color=969696>","<a href=https://CRAN.R-project.org/package=ellipse>ellipse<\/a> (0.4.1)<br>Maintainer: Duncan Murdoch <murdoch@stats.uwo.ca><br>imports/imported by:0/28<br>depends/is dependency of:2/12<br>suggests/suggested by:1/18<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ellipse?color=969696>","<a href=https://CRAN.R-project.org/package=emmeans>emmeans<\/a> (1.2.1)<br>Maintainer: Russell Lenth <russell-lenth@uiowa.edu><br>imports/imported by:12/5<br>depends/is dependency of:0/1<br>suggests/suggested by:15/3<br>enhances/enhaced by:11/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/emmeans?color=969696>","<a href=https://CRAN.R-project.org/package=emulator>emulator<\/a> (1.2-17)<br>Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com><br>imports/imported by:0/3<br>depends/is dependency of:1/5<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/emulator?color=969696>","<a href=https://CRAN.R-project.org/package=EpiBayes>EpiBayes<\/a> (0.1.2)<br>Maintainer: Matthew Branan <matthew.branan@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/EpiBayes?color=969696>","<a href=https://CRAN.R-project.org/package=epiR>epiR<\/a> (0.9-96)<br>Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au><br>imports/imported by:2/5<br>depends/is dependency of:1/2<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/epiR?color=969696>","<a href=https://CRAN.R-project.org/package=EurosarcBayes>EurosarcBayes<\/a> (1.1)<br>Maintainer: Peter Dutton <dutton.peter@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:6/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/EurosarcBayes?color=969696>","<a href=https://CRAN.R-project.org/package=evdbayes>evdbayes<\/a> (1.1-1)<br>Maintainer: Mathieu Ribatet <mathieu.ribatet@univ-montp2.fr><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/evdbayes?color=969696>","<a href=https://CRAN.R-project.org/package=evidence>evidence<\/a> (0.8.10)<br>Maintainer: Robert van Hulst <rvhulst@ubishops.ca><br>imports/imported by:2/0<br>depends/is dependency of:8/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/evidence?color=969696>","<a href=https://CRAN.R-project.org/package=evir>evir<\/a> (1.7-4)<br>Maintainer: Bernhard Pfaff <bernhard@pfaffikus.de><br>imports/imported by:0/2<br>depends/is dependency of:1/2<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/evir?color=969696>","<a href=https://CRAN.R-project.org/package=evolqg>evolqg<\/a> (0.2-5)<br>Maintainer: Diogo Melo <diogro@usp.br><br>imports/imported by:17/0<br>depends/is dependency of:1/0<br>suggests/suggested by:6/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/evolqg?color=969696>","<a href=https://CRAN.R-project.org/package=ExceedanceTools>ExceedanceTools<\/a> (1.2.2)<br>Maintainer: Joshua French <joshua.french@ucdenver.edu><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ExceedanceTools?color=969696>","<a href=https://CRAN.R-project.org/package=extrafont>extrafont<\/a> (0.17)<br>Maintainer: Winston Chang <winston@stdout.org><br>imports/imported by:4/10<br>depends/is dependency of:0/2<br>suggests/suggested by:1/10<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/extrafont?color=969696>","<a href=https://CRAN.R-project.org/package=fdrDiscreteNull>fdrDiscreteNull<\/a> (1.3)<br>Maintainer: Xiongzhi Chen <xiongzhi.chen@wsu.edu><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/fdrDiscreteNull?color=969696>","<a href=https://CRAN.R-project.org/package=ff>ff<\/a> (2.2-14)<br>Maintainer: Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com><br>imports/imported by:0/12<br>depends/is dependency of:2/9<br>suggests/suggested by:1/7<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ff?color=969696>","<a href=https://CRAN.R-project.org/package=fields>fields<\/a> (9.6)<br>Maintainer: Douglas Nychka <douglasnychka@gmail.com><br>imports/imported by:0/100<br>depends/is dependency of:3/35<br>suggests/suggested by:0/35<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/fields?color=969696>","<a href=https://CRAN.R-project.org/package=fitteR>fitteR<\/a> (0.1.0)<br>Maintainer: Markus Boenn <markus.boenn.sf@gmail.com><br>imports/imported by:7/0<br>depends/is dependency of:1/0<br>suggests/suggested by:66/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/fitteR?color=969696>","<a href=https://CRAN.R-project.org/package=foreach>foreach<\/a> (1.4.4)<br>Maintainer: Rich Calaway <richcala@microsoft.com><br>imports/imported by:3/297<br>depends/is dependency of:0/81<br>suggests/suggested by:1/60<br>enhances/enhaced by:4/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/foreach?color=969696>","<a href=https://CRAN.R-project.org/package=foreign>foreign<\/a> (0.8-70)<br>Maintainer: R Core Team <R-core@R-project.org><br>imports/imported by:3/42<br>depends/is dependency of:0/11<br>suggests/suggested by:0/41<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/foreign?color=969696>","<a href=https://CRAN.R-project.org/package=forestplot>forestplot<\/a> (1.7.2)<br>Maintainer: Max Gordon <max@gforge.se><br>imports/imported by:0/3<br>depends/is dependency of:3/4<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/forestplot?color=969696>","<a href=https://CRAN.R-project.org/package=Formula>Formula<\/a> (1.2-3)<br>Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org><br>imports/imported by:0/73<br>depends/is dependency of:1/35<br>suggests/suggested by:0/9<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Formula?color=969696>","<a href=https://CRAN.R-project.org/package=frontier>frontier<\/a> (1.1-2)<br>Maintainer: Arne Henningsen <arne.henningsen@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:2/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/frontier?color=969696>","<a href=https://CRAN.R-project.org/package=gamboostLSS>gamboostLSS<\/a> (2.0-0)<br>Maintainer: Benjamin Hofner <benjamin.hofner@pei.de><br>imports/imported by:4/1<br>depends/is dependency of:3/0<br>suggests/suggested by:5/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gamboostLSS?color=969696>","<a href=https://CRAN.R-project.org/package=gap>gap<\/a> (1.1-21)<br>Maintainer: Jing Hua Zhao <jinghua.zhao@mrc-epid.cam.ac.uk><br>imports/imported by:0/2<br>depends/is dependency of:0/0<br>suggests/suggested by:21/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gap?color=969696>","<a href=https://CRAN.R-project.org/package=gdata>gdata<\/a> (2.18.0)<br>Maintainer: Gregory R. Warnes <greg@warnes.net><br>imports/imported by:4/37<br>depends/is dependency of:0/18<br>suggests/suggested by:1/25<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gdata?color=969696>","<a href=https://CRAN.R-project.org/package=genetics>genetics<\/a> (1.3.8.1)<br>Maintainer: Gregory Warnes <greg@warnes.net><br>imports/imported by:0/4<br>depends/is dependency of:5/6<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/genetics?color=969696>","<a href=https://CRAN.R-project.org/package=geoBayes>geoBayes<\/a> (0.5.1)<br>Maintainer: Evangelos Evangelou <e.evangelou@maths.bath.ac.uk><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/geoBayes?color=969696>","<a href=https://CRAN.R-project.org/package=geoR>geoR<\/a> (1.7-5.2)<br>Maintainer: Paulo J. Ribeiro Jr <paulojus@ufpr.br><br>imports/imported by:5/11<br>depends/is dependency of:2/9<br>suggests/suggested by:4/13<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/geoR?color=969696>","<a href=https://CRAN.R-project.org/package=GGally>GGally<\/a> (1.4.0)<br>Maintainer: Barret Schloerke <schloerke@gmail.com><br>imports/imported by:9/32<br>depends/is dependency of:1/2<br>suggests/suggested by:17/16<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/GGally?color=969696>","<a href=https://CRAN.R-project.org/package=ggdmc>ggdmc<\/a> (0.1.3.9)<br>Maintainer: Yi-Shin Lin <yishin.lin@utas.edu.au><br>imports/imported by:9/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/ggdmc?color=969696>","<a href=https://CRAN.R-project.org/package=ggmcmc>ggmcmc<\/a> (1.1)<br>Maintainer: Xavier Fernández i Marín <xavier.fim@gmail.com><br>imports/imported by:1/3<br>depends/is dependency of:3/0<br>suggests/suggested by:8/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ggmcmc?color=969696>","<a href=https://CRAN.R-project.org/package=ggplot2>ggplot2<\/a> (2.2.1)<br>Maintainer: Hadley Wickham <hadley@rstudio.com><br>imports/imported by:10/983<br>depends/is dependency of:0/281<br>suggests/suggested by:17/494<br>enhances/enhaced by:1/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ggplot2?color=969696>","<a href=https://CRAN.R-project.org/package=ggridges>ggridges<\/a> (0.5.0)<br>Maintainer: Claus O. Wilke <wilke@austin.utexas.edu><br>imports/imported by:5/8<br>depends/is dependency of:0/1<br>suggests/suggested by:11/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ggridges?color=969696>","<a href=https://CRAN.R-project.org/package=ggthemes>ggthemes<\/a> (3.5.0)<br>Maintainer: Jeffrey B. Arnold <jeffrey.arnold@gmail.com><br>imports/imported by:7/22<br>depends/is dependency of:1/2<br>suggests/suggested by:13/14<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ggthemes?color=969696>","<a href=https://CRAN.R-project.org/package=GIGrvg>GIGrvg<\/a> (0.5)<br>Maintainer: Josef Leydold <josef.leydold@wu.ac.at><br>imports/imported by:0/3<br>depends/is dependency of:0/4<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/GIGrvg?color=969696>","<a href=https://CRAN.R-project.org/package=glmmTMB>glmmTMB<\/a> (0.2.1.0)<br>Maintainer: Mollie Brooks <mollieebrooks@gmail.com><br>imports/imported by:5/2<br>depends/is dependency of:0/0<br>suggests/suggested by:12/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/glmmTMB?color=969696>","<a href=https://CRAN.R-project.org/package=glmnet>glmnet<\/a> (2.0-16)<br>Maintainer: Trevor Hastie <hastie@stanford.edu><br>imports/imported by:1/112<br>depends/is dependency of:3/50<br>suggests/suggested by:3/50<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/glmnet?color=969696>","<a href=https://CRAN.R-project.org/package=googleVis>googleVis<\/a> (0.6.2)<br>Maintainer: Markus Gesmann <markus.gesmann@googlemail.com><br>imports/imported by:3/8<br>depends/is dependency of:0/0<br>suggests/suggested by:5/8<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/googleVis?color=969696>","<a href=https://CRAN.R-project.org/package=gpclib>gpclib<\/a> (1.5-5)<br>Maintainer: Roger D. Peng <rpeng@jhsph.edu><br>imports/imported by:1/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/7<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gpclib?color=969696>","<a href=https://CRAN.R-project.org/package=GPfit>GPfit<\/a> (1.0-0)<br>Maintainer: Hugh Chipman <hugh.chipman@acadiau.ca><br>imports/imported by:2/3<br>depends/is dependency of:0/0<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/GPfit?color=969696>","<a href=https://CRAN.R-project.org/package=gplots>gplots<\/a> (3.0.1)<br>Maintainer: Gregory R. Warnes <greg@warnes.net><br>imports/imported by:5/75<br>depends/is dependency of:0/30<br>suggests/suggested by:2/27<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gplots?color=969696>","<a href=https://CRAN.R-project.org/package=graph>graph<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/30<br>depends/is dependency of:0/15<br>suggests/suggested by:0/23<br>enhances/enhaced by:0/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/graph?color=969696>","<a href=https://CRAN.R-project.org/package=graphics>graphics<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/1299<br>depends/is dependency of:0/291<br>suggests/suggested by:0/39<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/graphics?color=969696>","<a href=https://CRAN.R-project.org/package=gRbase>gRbase<\/a> (1.8-3)<br>Maintainer: Søren Højsgaard <sorenh@math.aau.dk><br>imports/imported by:6/8<br>depends/is dependency of:1/4<br>suggests/suggested by:3/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:3/1<br><img src=https://cranlogs.r-pkg.org/badges/gRbase?color=969696>","<a href=https://CRAN.R-project.org/package=grDevices>grDevices<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/847<br>depends/is dependency of:0/132<br>suggests/suggested by:0/34<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/grDevices?color=969696>","<a href=https://CRAN.R-project.org/package=greta>greta<\/a> (0.2.3)<br>Maintainer: Nick Golding <nick.golding.research@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:11/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/greta?color=969696>","<a href=https://CRAN.R-project.org/package=grid>grid<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/300<br>depends/is dependency of:0/76<br>suggests/suggested by:0/60<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/grid?color=969696>","<a href=https://CRAN.R-project.org/package=gridExtra>gridExtra<\/a> (2.3)<br>Maintainer: Baptiste Auguie <baptiste.auguie@gmail.com><br>imports/imported by:5/182<br>depends/is dependency of:0/18<br>suggests/suggested by:5/87<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gridExtra?color=969696>","<a href=https://CRAN.R-project.org/package=gset>gset<\/a> (1.1.0)<br>Maintainer: Fang Liu <fang.liu.131@nd.edu><br>imports/imported by:0/0<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gset?color=969696>","<a href=https://CRAN.R-project.org/package=gtools>gtools<\/a> (3.5.0)<br>Maintainer: Gregory R. Warnes <greg@warnes.net><br>imports/imported by:0/98<br>depends/is dependency of:0/40<br>suggests/suggested by:0/14<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gtools?color=969696>","<a href=https://CRAN.R-project.org/package=gWidgets>gWidgets<\/a> (0.0-54)<br>Maintainer: John Verzani <jverzani@gmail.com><br>imports/imported by:0/20<br>depends/is dependency of:2/19<br>suggests/suggested by:1/7<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gWidgets?color=969696>","<a href=https://CRAN.R-project.org/package=gWidgetsRGtk2>gWidgetsRGtk2<\/a> (0.0-86)<br>Maintainer: John Verzani <jverzani@gmail.com><br>imports/imported by:0/13<br>depends/is dependency of:7/15<br>suggests/suggested by:0/9<br>enhances/enhaced by:1/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/gWidgetsRGtk2?color=969696>","<a href=https://CRAN.R-project.org/package=harvestr>harvestr<\/a> (0.7.1)<br>Maintainer: Andrew Redd <andrew.redd@hsc.utah.edu><br>imports/imported by:5/1<br>depends/is dependency of:0/0<br>suggests/suggested by:7/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/harvestr?color=969696>","<a href=https://CRAN.R-project.org/package=hBayesDM>hBayesDM<\/a> (0.5.0)<br>Maintainer: Woo-Young Ahn <wooyoung.ahn@gmail.com><br>imports/imported by:6/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hBayesDM?color=969696>","<a href=https://CRAN.R-project.org/package=HBglm>HBglm<\/a> (0.1)<br>Maintainer: Asad Hasan <asad.hasan@sentrana.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HBglm?color=969696>","<a href=https://CRAN.R-project.org/package=HDInterval>HDInterval<\/a> (0.1.3)<br>Maintainer: Mike Meredith <mmeredith@wcs.org><br>imports/imported by:0/1<br>depends/is dependency of:0/2<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HDInterval?color=969696>","<a href=https://CRAN.R-project.org/package=heatmaply>heatmaply<\/a> (0.14.1)<br>Maintainer: Tal Galili <tal.galili@gmail.com><br>imports/imported by:16/2<br>depends/is dependency of:2/1<br>suggests/suggested by:5/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/heatmaply?color=969696>","<a href=https://CRAN.R-project.org/package=hett>hett<\/a> (0.3-1)<br>Maintainer: Julian Taylor <julian.taylor@adelaide.edu.au><br>imports/imported by:0/1<br>depends/is dependency of:2/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hett?color=969696>","<a href=https://CRAN.R-project.org/package=HI>HI<\/a> (0.4)<br>Maintainer: Giovanni Petris <GPetris@Uark.edu><br>imports/imported by:0/3<br>depends/is dependency of:0/2<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HI?color=969696>","<a href=https://CRAN.R-project.org/package=HKprocess>HKprocess<\/a> (0.0-2)<br>Maintainer: Hristos Tyralis <montchrister@gmail.com><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HKprocess?color=969696>","<a href=https://CRAN.R-project.org/package=hmi>hmi<\/a> (0.9.11)<br>Maintainer: Matthias Speidel <matthias.speidel@googlemail.com><br>imports/imported by:19/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hmi?color=969696>","<a href=https://CRAN.R-project.org/package=Hmisc>Hmisc<\/a> (4.1-1)<br>Maintainer: Frank E Harrell Jr <f.harrell@vanderbilt.edu><br>imports/imported by:15/104<br>depends/is dependency of:4/41<br>suggests/suggested by:8/65<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Hmisc?color=969696>","<a href=https://CRAN.R-project.org/package=HPbayes>HPbayes<\/a> (0.1)<br>Maintainer: Dave Sharrow <dsharrow@u.washington.edu><br>imports/imported by:0/0<br>depends/is dependency of:6/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HPbayes?color=969696>","<a href=https://CRAN.R-project.org/package=HWEBayes>HWEBayes<\/a> (1.4)<br>Maintainer: Jon Wakefield <jonno@u.washington.edu><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/HWEBayes?color=969696>","<a href=https://CRAN.R-project.org/package=hypergeo>hypergeo<\/a> (1.2-13)<br>Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com><br>imports/imported by:3/8<br>depends/is dependency of:1/2<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hypergeo?color=969696>","<a href=https://CRAN.R-project.org/package=hyperSpec>hyperSpec<\/a> (0.99-20171005)<br>Maintainer: Claudia Beleites <chemometrie@beleites.de><br>imports/imported by:4/2<br>depends/is dependency of:3/0<br>suggests/suggested by:17/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hyperSpec?color=969696>","<a href=https://CRAN.R-project.org/package=hzar>hzar<\/a> (0.2-5)<br>Maintainer: Graham Derryberry <asterion@alum.mit.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/hzar?color=969696>","<a href=https://CRAN.R-project.org/package=ICBayes>ICBayes<\/a> (1.1)<br>Maintainer: Chun Pan <chunpan2003@hotmail.com><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ICBayes?color=969696>","<a href=https://CRAN.R-project.org/package=icensBKL>icensBKL<\/a> (1.1)<br>Maintainer: Arnošt Komárek <arnost.komarek@mff.cuni.cz><br>imports/imported by:4/0<br>depends/is dependency of:3/0<br>suggests/suggested by:16/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/icensBKL?color=969696>","<a href=https://CRAN.R-project.org/package=icmm>icmm<\/a> (1.1)<br>Maintainer: Vitara Pungpapong <vitara@cbs.chula.ac.th><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/icmm?color=969696>","<a href=https://CRAN.R-project.org/package=idealstan>idealstan<\/a> (0.2.7)<br>Maintainer: Robert Kubinec <rmk7xy@virginia.edu><br>imports/imported by:11/0<br>depends/is dependency of:1/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:5/0<br><img src=https://cranlogs.r-pkg.org/badges/idealstan?color=969696>","<a href=https://CRAN.R-project.org/package=IDPmisc>IDPmisc<\/a> (1.1.17)<br>Maintainer: Rene Locher <rene.locher@zhaw.ch><br>imports/imported by:0/2<br>depends/is dependency of:3/1<br>suggests/suggested by:2/4<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/IDPmisc?color=969696>","<a href=https://CRAN.R-project.org/package=igraph>igraph<\/a> (1.2.1)<br>Maintainer: Gábor Csárdi <csardi.gabor@gmail.com><br>imports/imported by:7/246<br>depends/is dependency of:1/113<br>suggests/suggested by:8/76<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/igraph?color=969696>","<a href=https://CRAN.R-project.org/package=inline>inline<\/a> (0.3.15)<br>Maintainer: Dirk Eddelbuettel <edd@debian.org><br>imports/imported by:1/8<br>depends/is dependency of:0/4<br>suggests/suggested by:1/14<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/inline?color=969696>","<a href=https://CRAN.R-project.org/package=IPMpack>IPMpack<\/a> (2.1)<br>Maintainer: Sean McMahon <ipmpack@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:6/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/IPMpack?color=969696>","<a href=https://CRAN.R-project.org/package=Iso>Iso<\/a> (0.0-17)<br>Maintainer: Rolf Turner <r.turner@auckland.ac.nz><br>imports/imported by:0/4<br>depends/is dependency of:0/5<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/Iso?color=969696>","<a href=https://CRAN.R-project.org/package=jagsUI>jagsUI<\/a> (1.4.9)<br>Maintainer: Ken Kellner <contact@kenkellner.com><br>imports/imported by:7/1<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/jagsUI?color=969696>","<a href=https://CRAN.R-project.org/package=JMbayes>JMbayes<\/a> (0.8-71)<br>Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl><br>imports/imported by:8/0<br>depends/is dependency of:4/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/JMbayes?color=969696>","<a href=https://CRAN.R-project.org/package=jmv>jmv<\/a> (0.8.6.2)<br>Maintainer: Jonathon Love <jon@thon.cc><br>imports/imported by:20/1<br>depends/is dependency of:0/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/jmv?color=969696>","<a href=https://CRAN.R-project.org/package=JointAI>JointAI<\/a> (0.1.0)<br>Maintainer: Nicole S. Erler <n.erler@erasmusmc.nl><br>imports/imported by:3/0<br>depends/is dependency of:1/0<br>suggests/suggested by:4/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/JointAI?color=969696>","<a href=https://CRAN.R-project.org/package=jpeg>jpeg<\/a> (0.1-8)<br>Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org><br>imports/imported by:0/36<br>depends/is dependency of:0/5<br>suggests/suggested by:0/17<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/jpeg?color=969696>","<a href=https://CRAN.R-project.org/package=kinship2>kinship2<\/a> (1.6.4)<br>Maintainer: Jason Sinnwell <sinnwell.jason@mayo.edu><br>imports/imported by:3/10<br>depends/is dependency of:2/9<br>suggests/suggested by:0/6<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/kinship2?color=969696>","<a href=https://CRAN.R-project.org/package=knitr>knitr<\/a> (1.20)<br>Maintainer: Yihui Xie <xie@yihui.name><br>imports/imported by:7/138<br>depends/is dependency of:0/11<br>suggests/suggested by:20/2877<br>enhances/enhaced by:0/7<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/knitr?color=969696>","<a href=https://CRAN.R-project.org/package=label.switching>label.switching<\/a> (1.7)<br>Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr><br>imports/imported by:2/3<br>depends/is dependency of:0/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/label.switching?color=969696>","<a href=https://CRAN.R-project.org/package=labstats>labstats<\/a> (1.0.1)<br>Maintainer: Stanley E. Lazic <stan.lazic@cantab.net><br>imports/imported by:0/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/labstats?color=969696>","<a href=https://CRAN.R-project.org/package=languageR>languageR<\/a> (1.4.1)<br>Maintainer: R. H. Baayen <harald.baayen@uni-tuebingen.de><br>imports/imported by:1/0<br>depends/is dependency of:0/0<br>suggests/suggested by:12/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/languageR?color=969696>","<a href=https://CRAN.R-project.org/package=LaplacesDemon>LaplacesDemon<\/a> (16.1.0)<br>Maintainer: Henrik Singmann <singmann+LaplacesDemon@gmail.com><br>imports/imported by:5/7<br>depends/is dependency of:0/2<br>suggests/suggested by:1/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/LaplacesDemon?color=969696>","<a href=https://CRAN.R-project.org/package=lattice>lattice<\/a> (0.20-35)<br>Maintainer: Deepayan Sarkar <deepayan.sarkar@r-project.org><br>imports/imported by:5/219<br>depends/is dependency of:0/179<br>suggests/suggested by:3/201<br>enhances/enhaced by:1/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/lattice?color=969696>","<a href=https://CRAN.R-project.org/package=LearnBayes>LearnBayes<\/a> (2.15.1)<br>Maintainer: Jim Albert <albert@bgsu.edu><br>imports/imported by:0/4<br>depends/is dependency of:0/3<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/LearnBayes?color=969696>","<a href=https://CRAN.R-project.org/package=LFDR.MLE>LFDR.MLE<\/a> (1.0)<br>Maintainer: M. Padilla <padilla.mpf@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/LFDR.MLE?color=969696>","<a href=https://CRAN.R-project.org/package=LFDREmpiricalBayes>LFDREmpiricalBayes<\/a> (1.0)<br>Maintainer: Ali Karimnezhad <ali_karimnezhad@yahoo.com><br>imports/imported by:3/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/LFDREmpiricalBayes?color=969696>","<a href=https://CRAN.R-project.org/package=lhs>lhs<\/a> (0.16)<br>Maintainer: Rob Carnell <bertcarnell@gmail.com><br>imports/imported by:0/20<br>depends/is dependency of:0/6<br>suggests/suggested by:1/12<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/lhs?color=969696>","<a href=https://CRAN.R-project.org/package=lme4>lme4<\/a> (1.1-17)<br>Maintainer: Ben Bolker <bbolker+lme4@gmail.com><br>imports/imported by:10/109<br>depends/is dependency of:3/50<br>suggests/suggested by:12/89<br>enhances/enhaced by:0/4<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/lme4?color=969696>","<a href=https://CRAN.R-project.org/package=lmeNB>lmeNB<\/a> (1.3)<br>Maintainer: Yumi Kondo <y.kondo@stat.ubc.ca><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/lmeNB?color=969696>","<a href=https://CRAN.R-project.org/package=lmeNBBayes>lmeNBBayes<\/a> (1.3.1)<br>Maintainer: Yumi Kondo <y.kondo@stat.ubc.ca><br>imports/imported by:0/0<br>depends/is dependency of:0/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/lmeNBBayes?color=969696>","<a href=https://CRAN.R-project.org/package=loo>loo<\/a> (2.0.0)<br>Maintainer: Jonah Gabry <jsg2201@columbia.edu><br>imports/imported by:4/9<br>depends/is dependency of:0/1<br>suggests/suggested by:7/6<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/loo?color=969696>","<a href=https://CRAN.R-project.org/package=lsmeans>lsmeans<\/a> (2.27-62)<br>Maintainer: Russell Lenth <russell-lenth@uiowa.edu><br>imports/imported by:10/1<br>depends/is dependency of:1/1<br>suggests/suggested by:22/5<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/lsmeans?color=969696>","<a href=https://CRAN.R-project.org/package=ltbayes>ltbayes<\/a> (0.4)<br>Maintainer: Timothy R. Johnson <trjohns@uidaho.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:7/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/ltbayes?color=969696>","<a href=https://CRAN.R-project.org/package=magic>magic<\/a> (1.5-8)<br>Maintainer: \"Robin K. S. Hankin\" <hankin.robin@gmail.com><br>imports/imported by:0/21<br>depends/is dependency of:1/7<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/magic?color=969696>","<a href=https://CRAN.R-project.org/package=magrittr>magrittr<\/a> (1.5)<br>Maintainer: Stefan Milton Bache <stefan@stefanbache.dk><br>imports/imported by:0/505<br>depends/is dependency of:0/22<br>suggests/suggested by:2/98<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/magrittr?color=969696>","<a href=https://CRAN.R-project.org/package=MAMS>MAMS<\/a> (1.2)<br>Maintainer: Thomas Jaki <jaki.thomas@gmail.com><br>imports/imported by:0/0<br>depends/is dependency of:2/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MAMS?color=969696>","<a href=https://CRAN.R-project.org/package=manet>manet<\/a> (1.0)<br>Maintainer: Veronica Vinciotti <veronica.vinciotti@brunel.ac.uk><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/manet?color=969696>","<a href=https://CRAN.R-project.org/package=maps>maps<\/a> (3.3.0)<br>Maintainer: Alex Deckmyn <alex.deckmyn@meteo.be><br>imports/imported by:2/31<br>depends/is dependency of:0/30<br>suggests/suggested by:5/87<br>enhances/enhaced by:0/2<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/maps?color=969696>","<a href=https://CRAN.R-project.org/package=maptools>maptools<\/a> (0.9-2)<br>Maintainer: Roger Bivand <Roger.Bivand@nhh.no><br>imports/imported by:7/74<br>depends/is dependency of:1/26<br>suggests/suggested by:8/69<br>enhances/enhaced by:2/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/maptools?color=969696>","<a href=https://CRAN.R-project.org/package=mAr>mAr<\/a> (1.1-2)<br>Maintainer: S. M. Barbosa <susana.barbosa@fc.up.pt><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mAr?color=969696>","<a href=https://CRAN.R-project.org/package=markdown>markdown<\/a> (0.8)<br>Maintainer: Yihui Xie <xie@yihui.name><br>imports/imported by:2/20<br>depends/is dependency of:0/3<br>suggests/suggested by:2/24<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/markdown?color=969696>","<a href=https://CRAN.R-project.org/package=MASS>MASS<\/a> (7.3-50)<br>Maintainer: Brian Ripley <ripley@stats.ox.ac.uk><br>imports/imported by:1/785<br>depends/is dependency of:4/433<br>suggests/suggested by:4/420<br>enhances/enhaced by:0/5<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MASS?color=969696>","<a href=https://CRAN.R-project.org/package=MasterBayes>MasterBayes<\/a> (2.55)<br>Maintainer: Jarrod Hadfield <j.hadfield@ed.ac.uk><br>imports/imported by:2/0<br>depends/is dependency of:4/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MasterBayes?color=969696>","<a href=https://CRAN.R-project.org/package=Matrix>Matrix<\/a> (1.2-14)<br>Maintainer: Martin Maechler <mmaechler+Matrix@gmail.com><br>imports/imported by:6/449<br>depends/is dependency of:0/246<br>suggests/suggested by:2/78<br>enhances/enhaced by:4/7<br>linkingto/linked by:0/9<br><img src=https://cranlogs.r-pkg.org/badges/Matrix?color=969696>","<a href=https://CRAN.R-project.org/package=matrixcalc>matrixcalc<\/a> (1.0-3)<br>Maintainer: Frederick Novomestky <fnovomes@poly.edu><br>imports/imported by:0/42<br>depends/is dependency of:0/11<br>suggests/suggested by:0/7<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/matrixcalc?color=969696>","<a href=https://CRAN.R-project.org/package=MatrixModels>MatrixModels<\/a> (0.4-1)<br>Maintainer: Martin Maechler <mmaechler+Matrix@gmail.com><br>imports/imported by:3/4<br>depends/is dependency of:0/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MatrixModels?color=969696>","<a href=https://CRAN.R-project.org/package=matrixStats>matrixStats<\/a> (0.53.1)<br>Maintainer: Henrik Bengtsson <henrikb@braju.com><br>imports/imported by:0/63<br>depends/is dependency of:0/21<br>suggests/suggested by:4/9<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/matrixStats?color=969696>","<a href=https://CRAN.R-project.org/package=MBA>MBA<\/a> (0.0-9)<br>Maintainer: Andrew Finley <finleya@msu.edu><br>imports/imported by:0/7<br>depends/is dependency of:0/1<br>suggests/suggested by:1/2<br>enhances/enhaced by:0/0<br>linkingto/linked by:1/0<br><img src=https://cranlogs.r-pkg.org/badges/MBA?color=969696>","<a href=https://CRAN.R-project.org/package=mboost>mboost<\/a> (2.8-1)<br>Maintainer: Benjamin Hofner <benjamin.hofner@pei.de><br>imports/imported by:10/7<br>depends/is dependency of:4/6<br>suggests/suggested by:12/10<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mboost?color=969696>","<a href=https://CRAN.R-project.org/package=MBSGS>MBSGS<\/a> (1.1.0)<br>Maintainer: Benoit Liquet <benoit.liquet@qut.edu.au><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MBSGS?color=969696>","<a href=https://CRAN.R-project.org/package=MBSP>MBSP<\/a> (1.0)<br>Maintainer: Ray Bai <raybai07@ufl.edu><br>imports/imported by:0/0<br>depends/is dependency of:5/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MBSP?color=969696>","<a href=https://CRAN.R-project.org/package=mcmc>mcmc<\/a> (0.9-5)<br>Maintainer: Charles J. Geyer <charlie@stat.umn.edu><br>imports/imported by:2/5<br>depends/is dependency of:0/1<br>suggests/suggested by:2/3<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mcmc?color=969696>","<a href=https://CRAN.R-project.org/package=MCMC.OTU>MCMC.OTU<\/a> (1.0.10)<br>Maintainer: Mikhail V. Matz <matz@utexas.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMC.OTU?color=969696>","<a href=https://CRAN.R-project.org/package=MCMC.qpcr>MCMC.qpcr<\/a> (1.2.3)<br>Maintainer: Mikhail V. Matz <matz@utexas.edu><br>imports/imported by:0/0<br>depends/is dependency of:3/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMC.qpcr?color=969696>","<a href=https://CRAN.R-project.org/package=mcmc.utils>mcmc.utils<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/1<br>depends/is dependency of:0/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mcmc.utils?color=969696>","<a href=https://CRAN.R-project.org/package=MCMC4Extremes>MCMC4Extremes<\/a> (1.1)<br>Maintainer: Fernando Ferraz do Nascimento <fernandofn@ufpi.edu.br><br>imports/imported by:0/0<br>depends/is dependency of:1/0<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMC4Extremes?color=969696>","<a href=https://CRAN.R-project.org/package=MCMCglmm>MCMCglmm<\/a> (2.25)<br>Maintainer: Jarrod Hadfield <j.hadfield@ed.ac.uk><br>imports/imported by:4/2<br>depends/is dependency of:3/4<br>suggests/suggested by:4/7<br>enhances/enhaced by:0/3<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMCglmm?color=969696>","<a href=https://CRAN.R-project.org/package=MCMCpack>MCMCpack<\/a> (1.4-3)<br>Maintainer: Jong Hee Park <jongheepark@snu.ac.kr><br>imports/imported by:7/37<br>depends/is dependency of:3/19<br>suggests/suggested by:0/13<br>enhances/enhaced by:0/1<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMCpack?color=969696>","<a href=https://CRAN.R-project.org/package=mcmcplots>mcmcplots<\/a> (0.4.2)<br>Maintainer: S. McKay Curtis <s.mckay.curtis@gmail.com><br>imports/imported by:3/1<br>depends/is dependency of:1/0<br>suggests/suggested by:0/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mcmcplots?color=969696>","<a href=https://CRAN.R-project.org/package=MCMCprecision>MCMCprecision<\/a> (0.3.8)<br>Maintainer: Daniel W. Heck <heck@uni-mannheim.de><br>imports/imported by:6/0<br>depends/is dependency of:0/0<br>suggests/suggested by:1/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:4/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMCprecision?color=969696>","<a href=https://CRAN.R-project.org/package=mcmcr>mcmcr<\/a> (0.0.1)<br>Maintainer: Joe Thorley <joe@poissonconsulting.ca><br>imports/imported by:7/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mcmcr?color=969696>","<a href=https://CRAN.R-project.org/package=mcmcse>mcmcse<\/a> (1.3-2)<br>Maintainer: Dootika Vats <D.Vats@warwick.ac.uk><br>imports/imported by:3/3<br>depends/is dependency of:0/1<br>suggests/suggested by:3/1<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/mcmcse?color=969696>","<a href=https://CRAN.R-project.org/package=MCMCvis>MCMCvis<\/a> (0.11.0)<br>Maintainer: Casey Youngflesh <caseyyoungflesh@gmail.com><br>imports/imported by:6/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCMCvis?color=969696>","<a href=https://CRAN.R-project.org/package=MCPAN>MCPAN<\/a> (1.1-21)<br>Maintainer: Frank Schaarschmidt <schaarschmidt@biostat.uni-hannover.de><br>imports/imported by:7/1<br>depends/is dependency of:0/2<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MCPAN?color=969696>","<a href=https://CRAN.R-project.org/package=metafor>metafor<\/a> (2.0-0)<br>Maintainer: Wolfgang Viechtbauer <wvb@metafor-project.org><br>imports/imported by:5/21<br>depends/is dependency of:2/5<br>suggests/suggested by:17/10<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/metafor?color=969696>","<a href=https://CRAN.R-project.org/package=methods>methods<\/a> (NA)<br>Maintainer: NA<br>imports/imported by:0/1595<br>depends/is dependency of:0/767<br>suggests/suggested by:0/37<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/methods?color=969696>","<a href=https://CRAN.R-project.org/package=metRology>metRology<\/a> (0.9-26-2)<br>Maintainer: Stephen L R Ellison <s.ellison@lgc.co.uk><br>imports/imported by:4/3<br>depends/is dependency of:2/1<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/metRology?color=969696>","<a href=https://CRAN.R-project.org/package=mev>mev<\/a> (1.11)<br>Maintainer: Leo Belzile <leo.belzile@epfl.ch><br>imports/imported by:12/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/mev?color=969696>","<a href=https://CRAN.R-project.org/package=mgcv>mgcv<\/a> (1.8-23)<br>Maintainer: Simon Wood <simon.wood@r-project.org><br>imports/imported by:4/118<br>depends/is dependency of:1/48<br>suggests/suggested by:4/56<br>enhances/enhaced by:0/3<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mgcv?color=969696>","<a href=https://CRAN.R-project.org/package=MHadaptive>MHadaptive<\/a> (1.1-8)<br>Maintainer: Corey Chivers <corey.chivers@mail.mcgill.ca><br>imports/imported by:0/2<br>depends/is dependency of:1/2<br>suggests/suggested by:0/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MHadaptive?color=969696>","<a href=https://CRAN.R-project.org/package=MHTcop>MHTcop<\/a> (0.1.0)<br>Maintainer: Jonathan von Schroeder <jvs@uni-bremen.de><br>imports/imported by:6/0<br>depends/is dependency of:0/0<br>suggests/suggested by:3/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/MHTcop?color=969696>","<a href=https://CRAN.R-project.org/package=miceadds>miceadds<\/a> (2.11-87)<br>Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de><br>imports/imported by:12/3<br>depends/is dependency of:1/0<br>suggests/suggested by:15/7<br>enhances/enhaced by:0/0<br>linkingto/linked by:2/0<br><img src=https://cranlogs.r-pkg.org/badges/miceadds?color=969696>","<a href=https://CRAN.R-project.org/package=microbenchmark>microbenchmark<\/a> (1.4-4)<br>Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com><br>imports/imported by:2/0<br>depends/is dependency of:0/0<br>suggests/suggested by:2/64<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/microbenchmark?color=969696>","<a href=https://CRAN.R-project.org/package=miscF>miscF<\/a> (0.1-4)<br>Maintainer: Dai Feng <dai_feng@merck.com><br>imports/imported by:2/1<br>depends/is dependency of:2/1<br>suggests/suggested by:2/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/miscF?color=969696>","<a href=https://CRAN.R-project.org/package=mistat>mistat<\/a> (1.0-5)<br>Maintainer: Daniele Amberti <daniele.amberti@gmail.com><br>imports/imported by:5/0<br>depends/is dependency of:0/0<br>suggests/suggested by:19/0<br>enhances/enhaced by:0/0<br>linkingto/linked by:0/0<br><img src=https://cranlogs.r-pkg.org/badges/mistat?color=969696>","<a href=https://CRAN.R-project.org/package=MixSIAR>MixSIAR<\/a> (3.1.10)<br>Maintainer: Brian Stock <b1stock@ucsd.edu><br>imports/imported