Is out. On sourceforge. Along with a new rjags. Thanks Martyn. I’m looking forward to working my way through some of the improvements, which include block-updating of parameters in GLMs more use of R’s d/p/q family of functions for den...

Is out. On sourceforge. Along with a new rjags. Thanks Martyn. I’m looking forward to working my way through some of the improvements, which include block-updating of parameters in GLMs more use of R’s d/p/q family of functions for den...

INCREDIBLY SIMPLE CALCULATIONS MADE SIMPLE Yes, we all know how to calculate 15% or 20% exactly, but it’s fun to use tipping heuristics and even more fun to make crowded graphs of how they compare to each other. (Sorry for the junky chart. Open for suggestions, in the words of Tom Waits.) Here are a

How to use Eclipse and StatET to create a handy-dandy development environment for R. Using the Eclipse environment provides a nice colored-syntax script editor, an R console, and an object browser to let you peruse the variables you've put into memory....

The simple linear regression model considers the relationship between two variables and in many cases more information will be available that can be used to extend the model. For example, there might be a categorical variable (sometimes known as a covariate) that can be used to divide the data set to fit a separate linear

Steve Miller has posted his interview with Revolution's CEO Norman Nie at Information Management blogs. In the interview, Steve digs into Norman's motivations for taking on a new venture around R after his successes with SPSS and how what he learned there applies to Revolution Computing. Also up for discussion: the benefits and challenges of an open-source business model;...

This is the code to perform the Bhapkar V test. I've rapidly wrote it, in 2 hours. The code is then quite brutal and it could be done better. As soon as possible, I will correct it.WARNING: it works *ONLY* with 3 groups, for now!bhapkar.test.3g sample for(i in 1:length(data1)){sample }obs for(i in 1:length(data1)){obs }rank cplets vec for(i in 1:length(data1])){vec...

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