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].

AuthorKaspar Ru{f}{i}bach <kaspar.rufibach@gmail.com> and Samuel Mueller <samuel.mueller@sydney.edu.au>
Date of publication2016-07-13 10:19:42
MaintainerKaspar Rufibach <kaspar.rufibach@gmail.com>
LicenseGPL (>= 2)
Version2.0.5
http://www.kasparrufibach.ch, www.maths.usyd.edu.au/ut/people?who=S_Mueller

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Files in this package

smoothtail
smoothtail/NAMESPACE
smoothtail/NEWS
smoothtail/R
smoothtail/R/falk.r
smoothtail/R/generalizedPick.r
smoothtail/R/pgpd.r
smoothtail/R/rgpd.r
smoothtail/R/lambdaGenPick.r
smoothtail/R/falkMVUE.r
smoothtail/R/pickands.r
smoothtail/R/dgpd.r
smoothtail/R/qgpd.r
smoothtail/MD5
smoothtail/DESCRIPTION
smoothtail/man
smoothtail/man/pickands.Rd smoothtail/man/gpd.Rd smoothtail/man/lambdaGenPick.Rd smoothtail/man/generalizedPick.Rd smoothtail/man/falkMVUE.Rd smoothtail/man/smoothtail-package.Rd smoothtail/man/falk.Rd

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