pith. sign in

arxiv: 1507.00108 · v3 · pith:KWIJPP2Enew · submitted 2015-07-01 · 📊 stat.ME

Models for extremal dependence derived from skew-symmetric families

classification 📊 stat.ME
keywords processnon-stationaryprocessesdistributionsextremalextremal-skew-familiesskew-normal
0
0 comments X
read the original abstract

Skew-symmetric families of distributions such as the skew-normal and skew-$t$ represent supersets of the normal and $t$ distributions, and they exhibit richer classes of extremal behaviour. By defining a non-stationary skew-normal process, which allows the easy handling of positive definite, non-stationary covariance functions, we derive a new family of max-stable processes - the extremal-skew-$t$ process. This process is a superset of non-stationary processes that include the stationary extremal-$t$ processes. We provide the spectral representation and the resulting angular densities of the extremal-skew-$t$ process, and illustrate its practical implementation (Includes Supporting Information).

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.