Extreme value random variables

Most major stats packages offer some modeling and inference capability for extreme value random variables. Typically one finds such functionality within Survial Analysis types of routines. For example, SAS offers Proc LIFEREG procedure which fits parametric models to failure time data that can be right-, left-, or interval-censored for a variety of extreme value distributions. Additional related functionality can be found in Proc PHREG, Proc LIFETEST and Proc TPHREG. Another userful source for additional extreme value functionality not found in SAS or SPSS routines can be found in R. The following list of contributed packages addressing this topic include: evd, evdbayes, evir, extRemes and ismev. For example the evd package offers simulation, distribution, quantile and density functions to univariate and multivariate parametric extreme value distributions, and provides fitting functions which calculate maximum likelihood estimates for univariate and bivariate maxima models, and for univariate and bivariate threshold models. And the evdbayes package offers functions for the Bayesian analysis of extreme value models, using MCMC
methods. Remaining listed R packages address topic such as: exploratory data analysis, block maxima, peaks over thresholds (univariate and bivariate), point
processes, gev/gpd distributions. …..now that is extreme…..

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