August 2017 New Package Picks

August was a relatively slow month for new R packages; “only” 180 new packages stuck to CRAN. Here are my “Top 40” picks organized into seven categories: Data, Machine Learning, Miscellaneous, Science, Statistics, Utilities and Visualizations. Although they have been written for specialized audiences, I have included the three “Science” packages because, in my layman’s opinion, they not only seem to be useful, but they are each documented well enough to give an interested person some idea of what they do.

Read more

Share Comments · · ·

Survival Analysis with R

With roots dating back to at least 1662 when John Graunt, a London merchant, published an extensive set of inferences based on mortality records, survival analysis is one of the oldest subfields of Statistics [1]. Basic life-table methods, including techniques for dealing with censored data, were discovered before 1700 [2], and in the early eighteenth century, the old masters - de Moivre working on annuities, and Daniel Bernoulli studying competing risks for the analysis of smallpox inoculation - developed the modern foundations of the field [2].

Read more

Share Comments · · · · ·

Report from Mexico City

Editors Note: It has been heartbreaking watching the images from México City. Teresa Ortiz, co-organizer of R-Ladies CDMX reports on efforts of data scientists to help. Our thoughts are with them, and with the people of México. It has been a hard couple of days around here. In less than 2 weeks, México has gone through two devastating earthquakes and the damages keep adding. Nevertheless, the response from the citizens has been outstanding and Mexican data-driven initiatives have not stayed behind.

Read more

Share Comments · · · ·

Enterprise-ready dashboards with Shiny and databases

Inside the enterprise, a dashboard is expected to have up-to-the-minute information, to have a fast response time despite the large amount of data that supports it, and to be available on any device. An end user may expect that clicking on a bar or column inside a plot will result in either a more detailed report, or a list of the actual records that make up that number. This article will cover how to use a set of R packages, along with Shiny, to meet those requirements.

Read more

Share Comments · · · · · ·

Asset Contribution to Portfolio Volatility

In our previous portfolio volatility work, we covered how to import stock prices, convert to returns and set weights, calculate portfolio volatility, and calculate rolling portfolio volatility. Now we want to break that total portfolio volatility into its constituent parts and investigate how each asset contributes to the volatility.

Read more

Share Comments · ·

Writing and Publishing my first R package

Inspired by the Community One of the themes at useR 2017 in Brussels was “Get involved”. People were encouraged to contribute to the community, even when they did not consider themselves R specialists (yet). This could be by writing a package or a blog post, but also by simply correcting typos through pull requests, or sending a tweet about a successful analysis. Bottom line: get your stuff out in the open.

Read more

Share Comments · · ·

RStudio::Conf 2018

It’s not even Labor Day, so it seems to be a bit early to start planning for next year’s R conferences. But, early-bird pricing for RStudio::Conf 2018 ends this Thursday. The conference which will be held in San Diego between January 31st and February 3rd promises to match and even surpass this year’s event. In addition to keynotes from Di Cook (Monash University and Iowa State University), J.J. Allaire (RStudio Founder, CEO & Principal Developer), Shiny creator Joe Cheng, and Chief Scientist Hadley Wickham, a number of knowledgeable (and entertaining) speakers have already committed including quant, long-time R user and twitter humorist JD Long (@CMastication), Stack Overflow’s David Robinson (@drob) and ProPublica editor Olga Pierce (@olgapierce).

Read more

Share Comments · ·

July 2017 New Package Picks

Two hundred and twenty-four new packages were added to CRAN in July. Below are my picks for the “Top 40” packages arranged in eight categories: Machine Learning, Science, Statistics, Numerical Methods, Statistics, Time Series, Utilities and Visualizations. Science and Numerical Methods are categories that I have not used before. The idea behind the Science category is to find a place for packages that appear to have been created with some particular scientific investigation or problem in mind.

Read more

Share Comments · · · ·

Control Systems Toolbox – System Interconnection

Introduction Dynamic systems are usually represented by a model before they can be analyzed computationally. These dynamic systems are systems that change, evolve or have their states altered or varied with time based on a set of defined rules. Dynamic systems could be mechanical, electrical, electronic, biological, sociological, and so on. Many such systems are usually defined by a set rules that are represented as a set of nonlinear differential equations.

Read more

Share Comments · · ·

Learning things we already know about stocks

This example groups stocks together in a network that highlights associations within and between the groups using only historical price data. The result is far from ground-breaking: you can already guess the output. For the most part, the stocks get grouped together into pretty obvious business sectors. Despite the obvious result, the process of teasing out latent groupings from historic price data is interesting.

Read more

Share Comments · · · · · ·