## 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> |

BugReports: |
NA |

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 |

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