Automatic robust Box-Cox and extended Yeo-Johnson transformations in regression

Marco Riani, Anthony C. Atkinson and Aldo Corbellini

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: The paper introduces an automatic procedure for the parametric transformation of the response in regression models to approximate normality. We consider the Box-Cox transformation and its generalization to the extended Yeo-Johnson transformation which allows for both positive and negative responses. A simulation study illuminates the superior comparative properties of our automatic procedure for the Box-Cox transformation. The usefulness of our procedure is demonstrated on four sets of data, two including negative observations. An important theoretical development is an extension of the Bayesian Information Criterion (BIC) to the comparison of models following the deletion of observations, the number deleted here depending on the transformation parameter.

Keywords: Bayesian Information Criterion (BIC); constructed variable; extended coefficient of determination (R2); forward search; negative observations; simultaneous test; Department of Statistics (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2023-03-01
New Economics Papers: this item is included in nep-ecm
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Published in Statistical Methods and Applications, 1, March, 2023, 32(1), pp. 75 - 102. ISSN: 1618-2510

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http://eprints.lse.ac.uk/114903/ Open access version. (application/pdf)

Related works:
Journal Article: Automatic robust Box–Cox and extended Yeo–Johnson transformations in regression (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:114903

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