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.

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.

Thanks,

Michael


Michael Haenlein
Professor of Marketing
ESCP Europe
Paris, France

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