Dear Michael. The normality of _covariates_ is seldom relevant. The relevance of normality of the _response variable_ depends on the model assumptions. In case of linear models the only the **residuals** (and not the responses) are assumed to be normally distributed.
Transformation of response or covariates can improve the fit of a model. In that case, knowledge about the link between covariates and response variables will help to pick relevant transformations. Best regards, ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium + 32 2 525 02 51 + 32 54 43 61 85 thierry.onkel...@inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens Michael Haenlein Verzonden: maandag 24 februari 2014 11:51 Aan: r-help@r-project.org CC: Michael Haenlein Onderwerp: [R] boxcox alternative 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 [[alternative HTML version deleted]] ______________________________________________ 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. * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * * Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document. ______________________________________________ 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.
