by Joseph Rickert One of the most interesting R related presentations at last week’s Strata Hadoop World Conference in New York City was the session on Distributed R by Sunil Venkayala and Indrajit Roy, both of HP Labs. In short, Distributed R is an open source project with the end goal of running R code in parallel on data...
Part 2 of a series by Daniel Hanson, with contributions by Steve Su (author of the GLDEX package) Recap of Part 1 In our previous article, we introduced the four-parameter Generalized Lambda Distribution (GLD) and looked at fitting a 20-year set of returns from the Wilshire 5000 Index, comparing the results of two methods, namely the Method of Moments,...
by Joseph Rickert In a recent post I talked about the information that can be developed by fitting a Tweedie GLM to a 143 million record version of the airlines data set. Since I started working with them about a year or so ago, I now see Tweedie models everywhere. Basically, any time I come across a histogram that...
by Daniel Hanson, with contributions by Steve Su (author of the GLDEX package). Part 1 of a series. Introduction As most readers are well aware, market return data tends to have heavier tails than that which can be captured by a normal distribution; furthermore, skewness will not be captured either. For this reason, a four parameter distribution such as...
by Joseph Rickert Recently, I had the opportunity to present a webinar on R and Data Science. The challenge with attempting this sort of thing is to say something interesting that does justice to the subject while being suitable for an audience that may include both experienced R users and curious beginners. The approach I settled on had three...
The following post by Norm Matloff originally appeared on his blog, Mad(Data)Scientist, on September 15th. We rarely republish posts that have appeared on other blogs, however, the questions that Norm raises both with respect to the teaching of statistics, and his assertion that "R's statistical procedures are centered far too much on significance testing" deserve a second look. Moreover,...
by Joseph Rickert One of the most difficult things about R, a problem that is particularly vexing to beginners, is finding things. This is an unintended consequence of R's spectacular, but mostly uncoordinated, organic growth. The R core team does a superb job of maintaining the stability and growth of the R language itself, but the innovation engine for...
by Matt Sundquist, Plotly Co-founder It's delightfully smooth to publish R code, plots, and presentations to the web. For example: Shiny makes interactive apps from R. Pretty R highlights R code for HTML. Slidify makes slides from R Markdown. Knitr and RPubs let you publish R Markdown docs. GitHub and devtools let you quickly release packages and collaborate. Now,...
by Joseph Rickert While preparing for the DataWeek R Bootcamp that I conducted this week I came across the following gem. This code, based directly on a Max Kuhn presentation of a couple years back, compares the efficacy of two machine learning models on a training data set. #----------------------------------------- # SET UP THE PARAMETER SPACE SEARCH GRID ctrl <-...
by Joseph Rickert The days are getting shorter here in California and the summer R conferences UseR!2014 and JSM are behind us, but there are still some very fine conferences for R users to look forward to before the year ends. DataWeek starts in San Francisco on September 15th. I will be conducting a bootcamp for new R users,...
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