Publications by Joseph Rickert
Highlights of the Milwaukee Workshop on R and Bioinformatics
by Joseph Rickert On May 10th and 11th, in honor of this being the International Year of Statistics, the Milwaukee Chapter of the American Statistical Association (MILWASA) held a workshop on cutting edge uses of R in Bioinformatics. One objective of the workshop was to show the “nuts and bolts” details of how R with C++ integration and the s...
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Ryan Sheftel: "R on the Trading Desk"
by Joseph Rickert In a post last week, I offered some first impressions about R/Finance 2013. Apparently, I was way off in estimating that 30% of the attendees were academics. The R/Finance organizers were quick to point out that percentage of academics attending the conference has been a constant 10% over the years; and this year was no differen...
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Intro to Parallel Random Number Generation with RevoScaleR
by Joseph Rickert Random number generation is fundamental to doing computational statistics. As you might expect, R is very rich in random number resources. The R base code provides several high quality random number generators including: Wichmann-Hill, Marsaglia-Multicarry, Super-Duper, Mersenne-Twister, Knuth-TAOCP-2002 and L’Ecuyer-CMRG. (Se...
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Mini-tutorial for Quandl: How to access financial data with R
by Joseph Rickert Quandl.com, the open source website for financial data, made rapid progress earlier this year in becoming an R friendly source for financial time series data. Tammer Kamel, Quandl’s founder introduced the site on Revolutions blog in late February as a “search engine” for numerical data and explained how Quandl’s “Q-bo...
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Draw nicer Classification and Regression Trees with the rpart.plot package
by Joseph Rickert The basic way to plot a classification or regression tree built with R’s rpart() function is just to call plot. However, in general, the results just aren’t pretty. As it turns out, for some time now there has been a better way to plot rpart() trees: the prp() function in Stephen Milborrow’s rpart.plot package. This funct...
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Learning Time Series with R
by Joseph Rickert Late last Saturday afternoon I was reading in my usual spot at the Dana Street Coffee House in Mt. View. A stranger walking by my table noticed my copy of Madsen’s Time Series Analysis (sitting there untouched again) said he needed to learn something about time series and asked if I could recommend a book. He looked serious so...
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rxDTree(): a new type of tree algorithm for big data
by Joseph Rickert The rxDTree() function included in the RevoScaleR package distributed with Revolution R Enterprise is an an example of a new class of algorithms that are being developed to deal with very large data sets. Although the particulars differ, what these algorithms have in common is the use of approximations, methods of summarizing or...
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Deepen your R experience with Rcpp
by Joseph Rickert It is very likely that even a very casual observer what is happening in the world of R these past few months would have come across some mention of Rcpp, the R package that greatly facilitates R and C++ integration. Rcpp is hot! Over 130 R packages now depend on Rcpp and it is likely to keep growing. The following plot built usi...
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Revolution Analytics Supports the R Community
by Joseph Rickert Early on, Revolution Analytics realized that R is more than just a tool for statistical computing — it is also the culture that has grown up around the use of the tool. The R culture is open and inclusive, competitive but also nourishing. There is a strong sense of community that encourages contribution and growth. We very muc...
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Statisticians: an endangered species?
by Joseph Rickert Every month I look forward to getting my copy of AMSTATNEWS, the monthly magazine of the American Statistical Association, in the mail. This July, I was both pleased and bemused by ASA President Marie Davidian’s article Aren’t We Data Science?. I was pleased to see a follow up to last month’s article The ASA and Big Data, ...
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