A suite of commands for fitting the skew-normal and skew-t models

dc.creatorMarchenko, Yulia V.
dc.creatorGenton, Marc G.
dc.date2017-04-01T19:27:57Z
dc.date.accessioned2026-07-09T07:45:24Z
dc.descriptionNonnormal data arise often in practice, prompting the development of flexible distributions for modeling such situations. In this article, we describe two multivariate distributions, the skew-normal and the skew-t, which can be used to model skewed and heavy-tailed continuous data. We then discuss some inferential issues that can arise when fitting these distributions to real data. We also consider the use of these distributions in a regression setting for more flexible parametric modeling of the conditional distribution given other predictors. We present commands for fitting univariate and multivariate skew-normal and skew-t regressions in Stata (skewnreg, skewtreg, mskewnreg, and mskewtreg) as well as some postestimation features (predict and skewrplot). We also demonstrate the use of the commands for the analysis of the famous Australian Institute of Sport data and U.S. precipitation data.
dc.identifierOther:st0207
dc.identifierdoi:10.22004/ag.econ.163393
dc.identifierhttps://ageconsearch.umn.edu/record/163393/files/sjart_st0207.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/163393
dc.identifier.urihttp://hdl.handle.net/123456789/591816
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/163393
dc.titleA suite of commands for fitting the skew-normal and skew-t models
dc.typeText

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