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').

Version: 1.1.0
Depends: R (≥ 2.14.0), methods, distrMod (≥ 2.7.0), ROptEst (≥ 1.1.0), robustbase, evd
Imports: RobAStRDA, distr, distrEx, RandVar, RobAStBase, startupmsg, actuar
Suggests: RUnit (≥ 0.4.26), ismev (≥ 1.39)
Published: 2018-08-03
Author: Nataliya 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], Peter Ruckdeschel [cre, aut, cph]
Maintainer: Peter Ruckdeschel <peter.ruckdeschel at>
License: LGPL-3
NeedsCompilation: yes
Citation: RobExtremes citation info
Materials: NEWS
CRAN checks: RobExtremes results


Reference manual: RobExtremes.pdf
Package source: RobExtremes_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: RobExtremes_1.1.0.tgz, r-oldrel: RobExtremes_1.1.0.tgz

Reverse dependencies:

Reverse enhances: distrMod


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