by Joseph Rickert If you type ?Distributions at the R console you get a list of the 21 probability distributions included in the stats package that ships with base R. The same list appears in the Introduction to R Manual on CRAN and in most of the many fine introductory books ... [Read more...]

by Joseph B. Rickert It is difficult to imagine that there is anyone on the planet with an internet connection and a desire to learn something new who has not at least looked into taking a massive open online course (MOOC). Last Fall, in an 11/4/12 article, the New York Time ... [Read more...]

A common criticism of R, especially from data scientists who are new to R but proficient in multiple programming languages, is that R is “quirky” and annoying because there is almost always more than one way to do simple things. I usually counter that they are trying to say that ... [Read more...]

By Joseph Rickert In a recent blog post, David Smith reported on a talk that Steve Yun and I gave at STRATA in NYC about building and benchmarking Poisson GLM models on various platforms. The results presented showed that the rxGlm function from Revolution Analytics’ RevoScaleR package running on a ... [Read more...]

You've probably heard of the Birthday Paradox: it only takes a small gathering of people before it's quite likely that two of them share the same birthday. You can solve the problem analytically or with simulation, but usually in either case simplifying assumptions are made (no-one born on February 29, for ... [Read more...]

By Joseph Rickert Revolution’s resident economist, Saar Golde, is very fond of saying that “90% of what you might from a recommendation engine can be achieved with simple techniques”. To illustrate this point (without doing a lot of work), we downloaded the million row movie dataset from www.grouplens.org ... [Read more...]

By Joseph Rickert Even to the practiced eye, looking at coefficients in R model summaries can be tedious. And, capturing information about the significance of coefficients from scores or maybe even hundreds of models in a way that makes writing the final report a bit easier is a time consuming ... [Read more...]

By Joseph Rickert Yesterday, the cosmic randomizer placed me next to a newly minter lawyer in a crowed Los Gatos coffee shop. In three minutes of conversation I learned that that the fellow was interested in corporate law, was about to take a job that would give him a seat ... [Read more...]

By Joseph Rickert Put up a poster that says something like “Data Mining with R” anywhere in the Bay Area and you will surely draw a crowd. But it was still a bit of a surprise that the monthly meeting of the Bay Area R User’s group was so ... [Read more...]

By Joseph Rickert Anyone seeking to learn R faces two major challenges: (1) learning how to swim in the sea of information: R packages, books, websites, blog posts, message boards etc. that threatens to drown a newbie and (2) and coming to grips with the structure, syntax and features of the language ... [Read more...]

(By Joseph Rickert.) In San Jose topics like big data, map reduce, predictive models, mobile analytics and crowdsourcing draw a crowd even on a Saturday. So it turned out that the ACM data Mining Camp and "un-conference" was a very "happening" way to spend a Saturday. Over 500 people attended the ... [Read more...]

(Contributing blogger Joe Rickert has put together a fantastic list of data sources suitable for use with R. If you're looking for data to use in the Applications of R Contest -- entries close October 31 -- this is a great resource for you -- Ed.) Hardly a day goes by ... [Read more...]

(Contributing blogger Joseph Rickert reports from the Stanford University Statistics Seminar series - ed.) Stanford University is very gracious about letting the general public attend many university events. Yesterday, it caught my eye that Bradley Efron was going to speak on Bayesian inference and the parametric bootstrap at the weekly ... [Read more...]

In this post Joseph Rickert demonstrates how to build a classification model on a large data set with the RevoScaleR package. A script file for use with Revolution R Enterprise to recreate the analysis below is at the end of the post, and can also be downloaded here -- ed. ... [Read more...]

The latest release of Revolution R Enterprise shows how Revolution Analytics’ package for big data, RevoScaleR, is continuing add new capabilities for Big Data statistics. RevoScaleR removes the limits on the size of the data that can be processed in R through the use of the highly efficient .Xdf binary ... [Read more...]

Are MLB players better hitters now than they were 20 years ago? Revolution Analytics' Joseph Rickert uses R to take a look at the data, and offers an instructive lesson in checking your assumptions for statistical tests in the process -- Ed. Data are everywhere – but, even for simple things, I ... [Read more...]

The recently announced Revolution Analytics / Zementis partnership goes a long way towards demonstrating how R fits into big-league production environments. A frequent complaint against R is that although R is fine prototyping tool it is not able to handle production environments. Well, that’s just not true. In fact, it ... [Read more...]

By guest blogger Joseph Rickert. I was very happy to be a part of the ACM Data Mining camp held last Saturday (November 13th) at eBay. It was a big day for discussing hot topics in data mining, Mahout, parallel SVMs etc, and also a pretty big day for R. ... [Read more...]

From guest blogger Joseph Rickert. Last night I went to hear Ken Krugler of Bixolabs talk about Hadoop at the monthly meeting of the Software Developers Forum. Maybe because Ken is an unusually lucid speaker, or maybe because I just reached some sort of cumulative tipping point through the prep ... [Read more...]

In the Introduction to his book “R for SAS and SPSS Users” (Springer 2009) Robert Muenchen offers ten reasons for learning R if you already know SAS or SPSS. All ten reasons say something important about R. However, his fourth reason: “R’s language is more powerful than SAS or SPSS. ... [Read more...]