Publications by Joseph Rickert
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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Ensemble Packages in R
by Mike Bowles Mike Bowles is a machine learning expert and serial entrepreneur. This is the second post in what is envisioned as a four part series that began with Mike's Thumbnail History of Ensemble Models. One of the main reasons for using R is the vast array of high-quality statistical algorithms available in R. Ensemble methods provide...
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Norm Matloff: Mad(Data)Scientist
by Joseph Rickert Norman Matloff professor of computer science at UC Davis, and founding member of the UCD Dept. of Statistics has begun posting as Mad(Data)Scientist. (You may know Norm from his book, The Art of R Programming: NSP, 2011.) In his second post (out today) on the new R package, freqparcoord, that he wrote with Yinkang Xie, Nor...
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BARUG talks highlight R’s diverse applications
by Joseph Rickert The seven lightning talks presented to the Bay Area useR Group on Tuesday night were not only really interesting (in some cases downright entertaining) in their own right, but they also illustrated the diversity of R applications, and the extent to which R has become embedded in the corporate world. Two presentations with a whim...
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Quantitative Finance Applications in R – 5: an Introduction to Monte Carlo Simulation
by Daniel Hanson Last time, we looked at the four-parameter Generalized Lambda Distribution, as a method of incorporating skew and kurtosis into an estimated distribution of market returns, and capturing the typical fat tails that the normal distribution cannot. Having said that, however, the Normal distribution can be useful in constructing Mo...
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Diving into H2O
by Joseph Rickert One of the remarkable features of the R language is its adaptability. Motivated by R’s popularity and helped by R’s expressive power and transparency developers working on other platforms display what looks like inexhaustible creativity in providing seamless interfaces to software that complements R’s strengths. The H2O R ...
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R Helps With Employee Churn
by Joseph Rickert Pasha Roberts, Chief Scientist at Talent Analytics, is writing a series of articles on Employee Churn for the Predictive Analytics Times that comprise a really instructive and valuable example of using R to do some basic predictive modeling. So far, Pasha has published Employee Churn 201 in which he makes a case for the importan...
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Predict which shoppers will become repeat buyers
by James P. Peruvankal Kaggle just announced a competition to predict which shoppers will become repeat buyers. To aid with algorithmic development, they have provided complete, basket-level, pre-offer shopping history for a large set of shoppers who were targeted for an acquisition campaign. Files containing the incentives offered to each shoppe...
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