Publications by Joseph Rickert
Some R News
by Joseph Rickert Here are a few things of some interest in the R world: The Gordon and Betty Moore Foundation has joined the R Consortium! This is a very positive development for the R Consortium and the R Community in general. The Moore Foundation has been a positive force for supporting technology that can make a real difference in people’s...
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Introducing sparklyr to the Madrid R User Group
by Carlos Ortega In the last meeting of 2016, the 40th in Madrid’s R Users Group five-year history, we had the opportunity to listen (via Skype) to a very interesting talk by Javier Luraschi, the main author of the package sparklyr. In our previous meeting, a colleague of the Community (José Luis Cañadas) made a first introduction to sparkly...
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The R Formula Method: The Good Parts
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 vari...
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Three Tips for Training Excel Users in R
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 th...
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Some Notes on the Cauchy Distribution
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. (No finite moments, anyway.) Be...
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January New Data Packages
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 Janua...
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More January Package Picks
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: Provide...
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The R Formula Method: The Bad Parts
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 variab...
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Madrid R User Group, A Brief History
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 our own help list R-help-es to regularly answers qu...
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February 2017 New Package Picks
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 tha...
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