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Recently I have run an exam where the following question had risen many problems for students (here I give its shortened formulation). You are given the data generating process y = 10x + e, where e is error term. Fit linear regression using lm, ne...

If, when writing code for a function, up to the current point in the code distinct local variables have been accessed for reading times (), will the next read access be from a previously unread local variable and if not what is the likelihood of choosing each of the distinct variables (global variables are ignored

Guerrilla alumnus Gary Little observed certain fixed-point behavior in simulations where disk IO blocks are updated randomly in a fixed size cache. For his python simulation with 10 million entries (corresponding to an allocation of about 400 MB of memory) the following results were obtained: Hit ratio (i.e., occupied) = 0.3676748 Miss ratio...

In case you missed them, here are some articles from April of particular interest to R users: A critique of a SAS whitepaper comparing the performance of SAS, R and Mahout. A video presentation from statistician Tess Nesbitt at UpStream, who uses GAM survival models in R for marketing attribution analysis. The April edition of the Revolution Analytics newsletter....

With Stéphane Tufféry, we were working this week on a chapter of a book, entitled Statistical Learning in Actuarial Science. The chapter should be based on R functions, and we wanted to reproduce some outputs he previously obtained with SAS. The good thing is that even complex functions (logistic regression, regression trees, etc) produce the same kind of outputs....

by Joseph Rickert Even a casual glance at the R Community Calendar shows an impressive amount of R user group activity throughout the world: 45 events in April and 31 scheduled so far for May. New groups formed last month in Knoxville, Tennessee (The Knoxville R User Group: KRUG) and Sheffield in the UK (The Sheffield R Users). An...

Previously, I talked about genetic algorithms (GA) for feature selection and illustrated the algorithm using a modified version of the GA R package and simulated data. The data were simulated with 200 non-informative predictors and 12 linear effects and three non-linear effects. Quadratic discriminant analysis (QDA) was used to model the data. The last set of...

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