Publications by Joseph Rickert
R User Groups Update
by Joseph Rickert After an end-of-year slow down in R user group acrtivity that lasted into mid January, the Revolution Analytics’ Community Calendar indicates that R user groups worldwide are back in full swing with 48 events listed in the short month of February. And, while the total number of active user groups has not grown from this time l...
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Emacs, ESS and R for Zombies
by Rodney Sparapani, PhD Rodney is an Assistant Professor in the Institute for Health and Society from the Division of Biostatistics at the Medical College of Wisconsin in Milwaukee and president of the Milwaukee Chapter of the ASA which is hosting an R workshop on Data Mining in Milwaukee on April 4th. Emacs Speaks Statistics (ESS) is a GPL sof...
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Getting Started with Hidden Markov Models in R
by Joseph Rickert In addition to the considerable benefit of being able to meet other, like-minded R users face-to-face, R user groups fill a niche in the world of R education by providing a forum for communicating technical information in an informal and engaging manner. Conferences such as useR!, JSM and countless smaller statistical meetings s...
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An R "meta" book
by Joseph Rickert I am a book person. I collect books on all sorts of subjects that interest me and consequently I have a fairly extensive collection of R books, many of which I find to be of great value. Nevertheless, when I am asked to recommend an R book to someone new to R I am usually flummoxed. R is growing at a fantastic rate, and people c...
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Secrets of Teaching R
by James Paul Peruvankal, Senior Program Manager at Revolution Analytics At Revolution Analytics, we are always interested in how people teach and learn R, and what makes R so popular, yet ‘quirky’ to learn. To get some insight from a real pro we interviewed Bob Muenchen. Bob is the author of R for SAS and SPSS Users and, with Joseph M. Hi...
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Data Sets for Data Science
by Joseph Rickert Recently, I had the opportunity to be a member of a job panel for Mathematics, Economics and Statistics students at my alma mater, CSUEB (California State University East Bay). In the context of preparing for a career in data science a student at the event asked: “Where can I find good data sets?”. This triggered a number of...
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A Thumbnail History of Ensemble Methods
By Mike Bowles Ensemble methods are the backbone of machine learning techniques. However, it can be a daunting subject for someone approaching it for the first time, so we asked Mike Bowles, machine learning expert and serial entrepreneur to provide some context. Ensemble Methods are among the most powerful and easiest to use of predictive analyt...
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R User Group Activity for Q1 2014
by Joseph Rickert Worldwide R user group activity for the first Quarter of 2014 appears to be way up compared to previous years as the following plot shows. The plot was built by counting the meetings on Revolution Analytics R Community Calendar. R users continue to value the live, in person events and face-to-face meetings with their peers. Mor...
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A look at R vectorization through the Collatz Conjecture
by Seth Mottaghinejad, Analytic Consultant for Revolution Analytics You may have heard before that R is a vectorized language, but what do we mean by that? One way to read that is to say that many functions in R can operate efficiently on vectors (in addition to singletons). Here are some examples: > log(1) # input and output are singletons[1] 0 ...
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Some R Resources for GLMs
by Joseph Rickert Generalized Linear Models have become part of the fabric of modern statistics, and logistic regression, at least, is a “go to” tool for data scientists building classification applications. The ready availability of good GLM software and the interpretability of the results logistic regression makes it a good baseline classif...
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