The email wasn’t a challenge but a simple question: Is it possible to run a multivariate analysis in multiple sites? I was going to answer yes, of course, and leave it there but it would be a cruel, non-satisfying answer. … Continue reading →

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This brief tutorial illustrates how to combine S4 object oriented capabilities with function closures in order to develop classes with built in methods. Thanks to Hadley Wickham for the great contribution of material and tutorials made available on the web and to Bill Venables and Stefano Iacus for their kind reviews. Regular … Continue reading →

Performance analysis of an example portfolio. The portfolio We explore a particular portfolio during 2007. It invests in S&P 500 stocks and starts the year with a value of $10 million. Initially there are 50 names in the portfolio. It also ends the year with 50 names but has up to 53 names during the … Continue reading...

Dear R-Users, a question: I am the author of the ‘qpcR’ package. Within this, there is a function ‘propagate’ that does error propagation based on Monte Carlo Simulation, permutation-based confidence intervals and Taylor expansion. For the latter I recently implemented a second-order Taylor expansion term that can correct for nonlinearity. The formulas are quite complex

Windows 95 transformed the PC software market and established Microsoft as the dominant player. Can Microsoft do it again? Can it use the release of Windows 8 to elevate its entire brand image? More importantly to some of us, can Microsoft use statistical modeling to help it achieve its goal?Of course, the answer depends on what you mean by...

Phylogenetic trees are a specialization of hierarchical clustering which elegantly capture relatedness between observations, grouping like with like. Yet hierarchical clusterings have one common complaint, as compared to density/distribution based clustering, the ability to classify the data into different types. … Continue reading →

The little half puzzle proposed a “dumb’ solution in that players play a minimax strategy. There are 34 starting values less than 100 guaranteeing a sure win to dumb players. If instead the players maximise their choice at each step, the R code looks like this: and there are now 66 (=100-34, indeed!) starting values