Michael, On Mon, Feb 24, 2014 at 5:51 AM, Michael Haenlein <haenl...@escpeurope.eu> wrote: > > Dear all, > > I am working with a set of variables that are very non-normally > distributed. To improve the performance of my model, I'm currently applying > a boxcox transformation to them. While this improves things, the > performance is still not great. >
Are these predictors that you are transforming? > So my question: Are there any alternatives to boxcox in R? I would need a > model that estimates the "best" transformation automatically without input > from the user since my approach should be flexible enough to deal with any > kind of distribution. boxcox allows me to do this by picking the lambda > that leads to the "best fit" but I wonder whether there are other options > out there. > If they are predictors, caret has a function called 'preProcess' that might interest you. See: http://caret.r-forge.r-project.org/preprocess.html#trans Max ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
