smoothtail: Smooth Estimation of GPD Shape Parameter

Given independent and identically distributed observations X(1), ..., X(n) from a Generalized Pareto distribution with shape parameter gamma in [-1,0], offers several estimates to compute estimates of gamma. The estimates are based on the principle of replacing the order statistics by quantiles of a distribution function based on a log–concave density function. This procedure is justified by the fact that the GPD density is log–concave for gamma in [-1,0].

Version: 2.0.5
Depends: logcondens (≥ 2.0.0)
Imports: stats
Published: 2016-07-13
Author: Kaspar Ru{f}{i}bach and Samuel Mueller
Maintainer: Kaspar Rufibach <kaspar.rufibach at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.kasparrufibach.ch, www.maths.usyd.edu.au/ut/people?who=S_Mueller
NeedsCompilation: no
Materials: NEWS
CRAN checks: smoothtail results

Documentation:

Reference manual: smoothtail.pdf

Downloads:

Package source: smoothtail_2.0.5.tar.gz
Windows binaries: r-devel: smoothtail_2.0.5.zip, r-release: smoothtail_2.0.5.zip, r-oldrel: smoothtail_2.0.5.zip
macOS binaries: r-release (arm64): smoothtail_2.0.5.tgz, r-oldrel (arm64): smoothtail_2.0.5.tgz, r-release (x86_64): smoothtail_2.0.5.tgz, r-oldrel (x86_64): smoothtail_2.0.5.tgz
Old sources: smoothtail archive

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