gp.fit: Maximum likelihood estimate of generalized Pareto applied to...

In mev: Modelling of Extreme Values

Maximum likelihood estimate of generalized Pareto applied to threshold exceedances

Description

The function fit.gpd is a wrapper around gp.fit

Usage

gp.fit(
  xdat,
  threshold,
  method = c("Grimshaw", "auglag", "nlm", "optim", "ismev", "zs", "zhang"),
  show = FALSE,
  MCMC = NULL,
  fpar = NULL,
  warnSE = TRUE
)

Arguments

xdat	a numeric vector of data to be fitted.
threshold	the chosen threshold.
method	the method to be used. See Details. Can be abbreviated.
show	logical; if TRUE (the default), print details of the fit.
MCMC	NULL for frequentist estimates, otherwise a boolean or a list with parameters passed. If TRUE, runs a Metropolis-Hastings sampler to get posterior mean estimates. Can be used to pass arguments niter, burnin and thin to the sampler as a list.
fpar	a named list with fixed parameters, either scale or shape
warnSE	logical; if TRUE, a warning is printed if the standard errors cannot be returned from the observed information matrix when the shape is less than -0.5.

mev documentation built on April 20, 2023, 5:10 p.m.