Multivariate log-skew-elliptical distributions with applications to precipitation data

Yulia V. Marchenko, Marc G. Genton

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

We introduce a family of multivariate log-skew-elliptical distributions, extending the list of multivariate distributions with positive support. We investigate their probabilistic properties such as stochastic representations, marginal and conditional distributions, and existence of moments, as well as inferential properties. We demonstrate, for example, that as for the log-t distribution, the positive moments of the log-skew-t distribution do not exist. Our emphasis is on two special cases, the log-skew-normal and log-skew-t distributions, which we use to analyze US national (univariate) and regional (multivariate) monthly precipitation data.

Original languageEnglish (US)
Pages (from-to)318-340
Number of pages23
JournalEnvironmetrics
Volume21
Issue number3-4
DOIs
StatePublished - May 2010
Externally publishedYes

Keywords

  • Climatic regions
  • Extreme events
  • Heavy tails
  • Log-skew-normal
  • Log-skew-t
  • Moments
  • Multivariate
  • Precipitation
  • Skewness

ASJC Scopus subject areas

  • Ecological Modeling
  • Statistics and Probability

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