Continuing in my exploration of the Russell 2000 (Russell 2000 Softail Fat Boy), I thought I would try to approach the topic with a low volatility paradox mindset. Since 2005, beta of the Russell 2000 compared to the S&P 500 has exceeded 1.2 ...

Model level fit summaries can be tricky in R. A quick read of model fit summary data for factor levels can be misleading. We describe the issue and demonstrate techniques for dealing with them.When modeling you often encounter what are commonly called categorical variables, which are called factors in R. Possible values of categorical variables Related posts:

Another release of Rcpp has just appeared on CRAN and was just uploaded to Debian. It addresses yet another issue we had on OS X and should hopefully put the build issues to rest. Three new (vectorized) sugar functions were added, along with some ne...

This post demonstrates the simplest Species Distribution Model based on logistic regression for presence/absence data. I heavily simplified the example from Kéry (2010): Introduction to WinBUGS for Ecologists, Chapter 20.Read more →

Another day full of interesting and challenging—in the sense they generated new questions for me—talks at the SuSTain workshop. After another (dry and fast) run around the Downs; Leo Held started the talks with one of my favourite topics, namely the theory of g-priors in generalized linear models. He did bring a new perspective on

I had a great time yesterday moderating the "R in Action" panel discussion at the DataWeek conference in San Francisco. Each of the panelists represented a company that is actively using R and/or Revolution R Enterprise. Here (from memory, since I couldn't take notes) are some the things they shared: Jesse Bridgewater from eBay talked about how R is...