August 2020: "Top 40" New CRAN Packages

One hundred forty-six new packages stuck to CRAN in August. Below, are my ‘Top 40’ picks in eleven categories: Computational Methods, Data, Genomics, Insurance, Machine Learning, Mathematics, Medicine, Statistics, Time Series, Utilities and Visualization.

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Some Thoughts on R / Medicine 2020

The third annual R / Medicine Conference was held online this year from August 27th to August 29th and was an unqualified success. The last minute pivot from small, in-person conference, which was to be held onsite at the Children’s Hospital of Philadelphia, CHOP, to a virtual event turned out to be a catalyst for positive change. Under the imaginative, and tireless leadership of conference chair Dr.

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Fake Data with R

In this post, I provide some reasons for why a statistician or data scientist might want to simulate synthetic or ‘fake’ data, and briefly examine several R packages that make this task a little easier.

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Crowd Counting Consortium Crowd Data and Shiny Dashboard

This post spotlights one of the most comprehensive open-source event data sets on protests, demonstrations, and other political gatherings in the contemporary U.S., along with a new GitHub repository and Shiny dashboard that make the data much easier to use and explore.

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July 2020: "Top 40" New CRAN Packages

Here are my picks for the ‘Top 40’ new CRAN packages for July 2020 in seven categories: Computational Methods, Data, Genomics, Machine Learning, Science, Statistics, and Utilities.

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R Package Integration with Modern Reusable C++ Code Using Rcpp - Part 5

We continue the tutorial on developing Rcpp implementations that keep both reusable and standard C++ code separate from the R interface. In Part 4, we went through the build processes for a simple package containing a single C++ .cpp file. In this post, we work through a more realistic case which involves multiple reusable C++ files and the C++ interface files that export functions to R.

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R Package Integration with Modern Reusable C++ Code Using Rcpp - Part 4

This post is a step by step guide for using the RStudio IDE to build an R package with integrated C++ code, and shows how to use exported functions from within an R session.

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Monitor COVID-19 at the COVID-19 Forecast Hub

If you are looking for a place to monitor expert forecasts for United States weekly and cumulative COVID-19 deaths, you can’t do any better than the Reich Lab (University of Massachusetts) COVID-19 Forecast Hub. The same is true for data scientists who may be seeking to publish their own forecasts and compare them with the work of their peers.

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Party with R: How the Community Enabled Us to Write a Book

The R community offers so many opportunities to get feedback, advice, and information from a wide variety of users. Early on in the book development, we had a lot of questions to nail down. We listened to the stories of many data scientists who work in education, then found common experiences we could describe in our writing.

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R Package Integration with Modern Reusable C++ Code Using Rcpp - Part 3

This post shows how to configure code that allows the use of standard reusable C++ in an R package, without having to modify it with any R or Rcpp-specific syntax.

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