RobExtremes: Optimally Robust Estimation for Extreme Value Distributions

Optimally robust estimation for extreme value distributions using S4 classes and methods (based on packages 'distr', 'distrEx', 'distrMod', 'RobAStBase', and 'ROptEst'); the underlying theoretic results can be found in Ruckdeschel and Horbenko, (2013 and 2012), \doi{10.1080/02331888.2011.628022} and \doi{10.1007/s00184-011-0366-4}.

Getting started

Package details

AuthorNataliya Horbenko [aut, cph], Bernhard Spangl [ctb] (contributed smoothed grid values of the Lagrange multipliers), Sascha Desmettre [ctb] (contributed smoothed grid values of the Lagrange multipliers), Eugen Massini [ctb] (contributed an interactive smoothing routine for smoothing the Lagrange multipliers and smoothed grid values of the Lagrange multipliers), Daria Pupashenko [ctb] (contributed MDE-estimation for GEV distribution in the framework of her PhD thesis 2011--14), Gerald Kroisandt [ctb] (contributed testing routines), Matthias Kohl [aut, cph] (<https://orcid.org/0000-0001-9514-8910>), Peter Ruckdeschel [cre, aut, cph] (<https://orcid.org/0000-0001-7815-4809>)
MaintainerPeter Ruckdeschel <peter.ruckdeschel@uni-oldenburg.de>
LicenseLGPL-3
Version1.3.1
URL https://r-forge.r-project.org/projects/robast/
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("RobExtremes", repos="http://R-Forge.R-project.org")

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RobExtremes documentation built on Aug. 30, 2024, 3:01 a.m.