We are less than one month away from the R/Medicine conference! Tickets are still available to connect with the R users who are advancing the way we think about human health. The goal of the R/Medicine conference is to promote the use of th...

by Joseph Rickert Few of us have enough time to read, and most of us already have depressingly deep stacks of material that we would like to get through. However, sometimes a random encounter with something interesting is all that it takes to regenerate enthusiasm. Just in case you are not going to get to

by Joseph Rickert One hundred and forty-five new packages were added to CRAN in February. Here are 47 interesting packages organized into five categories; Biostatistics, Data, Data Science, Statistics and Utilities. Biostatistics BaTFLED3D v0.1.7: Implements a machine learning algorithm to make predictions and determine interactions in data that varies along three independent modes. It was

by Carlos Ortega (Editors note: A Spanish verison of the post follows the English text) In the first meeting we were 5, now we are consistently over 60. It was not difficult for us to start up the group of users of R of Madrid. Gregorio Serrano, Carlos Gil Bellosta, Pedro Concejero and I started

R’s model formula infrastructure was discussed in my previous post. Despite the elegance and convenience of the formula method, there are some aspects that are limiting. Limitations to Extensibility The model formula interface does have some limitations: It can be kludgy with many operations on many variables (e.g., log transforming 50 variables via a formula

by Joseph Rickert In a recent post, I highlighted several new packages that arrived on CRAN in January that provided R users with access to data. In this post, I present additional selections for interesting January packages, organized into the categories Miscellaneous, Machine Learning, Statistics and Utilities. Miscellaneous rcss v1.2: Provides functions for Solving Control

by Joseph Rickert As forecast, the number of R packages hosted on CRAN exceeded 10,000 in January. Dirk Eddelbuettel, who tracks what’s happening on CRAN with his CRANberries site, called hurricaneexposure the 10,000th package in a tweet on January 27th. hurricaneexposure was one of two hundred and six new packages that arrived on CRAN in

by Joseph Rickert I have always been attracted to the capricious. So, it was no surprise that I fell for the Cauchy distribution at first sight. I had never seen such unpredictability! You might say that every distribution has its moments of unpredictability, but the great charm of Cauchy is that it has no moments.

by Merav Yuravlivker, CEO of Data Society “I’m not a coder” or “I was never good at math” is a frequent refrain I hear when I ask professionals about their data analysis skills. Through popular culture and stereotypes, most people who don’t have a background in programming automatically underestimate their ability to create amazing things

by Max Kuhn Introduction The formula interface to symbolically specify blocks of data is ubiquitous in R. It is commonly used to generate design matrices for modeling function (e.g. lm). In traditional linear model statistics, the design matrix is the two-dimensional representation of the predictor set where instances of data are in rows and variable

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