extRemes

Extreme Value Analysis

Last update: 2 February 2024

Copyright license: GNU General Public License, version 3.0, GNU General Public License, version 2.0

Software version identifier: 2.1-3, 2.1-4

Source code repository: https://github.com/cran/extRemes

Description

General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) <doi:10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi:10.1175/JTECH-D-20-0070.1>.

Cites work

Related Items (14)

How do mobility restrictions and social distancing during COVID-19 affect oil price? ⋮ Comparison of trend detection methods in GEV models ⋮ Spatial modelling of risk premiums for water damage insurance ⋮ MCMC4Extremes: an R package for Bayesian inference for extremes and its extensions ⋮ Predicting federal funds rate using extreme value theory ⋮ Extreme quantiles and tail index of a distribution based on kernel estimator ⋮ extremeStat ⋮ Unnamed Item ⋮ Effects of stochastic parametrization on extreme value statistics ⋮ Is human life limited or unlimited? (A discussion of the paper by Holger Rootzén and Dmitrii Zholud) ⋮ Robust interval forecasting algorithm based on a probabilistic cluster model ⋮ Determinants of high crude oil price: a nonstationary extreme value approach ⋮ climextRemes ⋮ in2extRemes

This page was built for software: extRemes