texmex (2.4.5)

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Statistical Modelling of Extreme Values.


Statistical extreme value modelling of threshold excesses, maxima and multivariate extremes. Univariate models for threshold excesses and maxima are the Generalised Pareto, and Generalised Extreme Value model respectively. These models may be fitted by using maximum (optionally penalised-)likelihood, or Bayesian estimation, and both classes of models may be fitted with covariates in any/all model parameters. Model diagnostics support the fitting process. Graphical output for visualising fitted models and return level estimates is provided. For serially dependent sequences, the intervals declustering algorithm of Ferro and Segers (2003) is provided, with diagnostic support to aid selection of threshold and declustering horizon. Multivariate modelling is performed via the conditional approach of Heffernan and Tawn (2004) , with graphical tools for threshold selection and to diagnose estimation convergence.

Maintainer: Harry Southworth
Author(s): Harry Southworth [aut, cre], Janet E. Heffernan [aut], Paul D. Metcalfe [aut], Yiannis Papastathopoulos [ctb], Alec Stephenson [ctb], Stuart Coles [ctb]

License: GPL (>= 2)

Uses: ggplot2, mvtnorm, Rcpp, ismev, lattice, survival, MASS, testthat, gridExtra, devtools, knitr, dplyr, tidyr
Reverse suggests: lax

Released about 1 month ago.

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