oogpd.fit: Maximum-likelihood Fitting of the Generalized Pareto...

In RuoqingYin/oolax: Object-orientated Loglikelihood Adjustment for Extreme Value Models

Description

This is a slightly modified version of the gpd.fit function in the ismev package. The modification is to add to the returned object the arguments xdat, threshold, ydat, siglink, shlink and matrices sigmat, shmat giving the respective regression design matrices for the scale and shape parameters of the model.

Usage

oogpd.fit(xdat, threshold, npy = 365, ydat = NULL, sigl = NULL,
  shl = NULL, siglink = identity, shlink = identity,
  siginit = NULL, shinit = NULL, show = TRUE,
  method = "Nelder-Mead", maxit = 10000, ...)

References

Heffernan, J. E. and Stephenson, A. G. (2018). ismev: An Introduction to Statistical Modeling of Extreme Values. R package version 1.42. https://CRAN.R-project.org/package=ismev.

Examples

got_ismev <- requireNamespace("ismev", quietly = TRUE)
if (got_ismev) {
  data(rain)
  fit1 <- gpd.fit(rain, 10, show = FALSE)
  ls(fit1)
  fit2 <- oogpd.fit(rain, 10, show = FALSE)
  ls(fit2)
}

RuoqingYin/oolax documentation built on May 28, 2019, 12:20 p.m.