extGP.fit: Fitting the extended GP model

In mbtgy/tcG: Fitting meta-Gaussian models

Fitting the extended GP model

Description

Fitting the extended GP model

Usage

extGP.fit(
  y,
  init,
  ym = 0,
  step = 0,
  bootstrap = TRUE,
  R = 500,
  plots = TRUE,
  filename = NULL,
  ncpus = parallel::detectCores(),
  ym.param = FALSE
)

Arguments

y	vector of positive data
init	initialisation parameters, a vector of length 3
ym	minimal value that can be observed
step	discretization step
bootstrap	boolean, should boostrap replicates be fitted?
R	number of bootstrap replicates
plots	boolean, should plots be drawn?
filename	if you want to save the plots, a character for your file's name
ncpus	number of cores
ym.param	boolean, should ym be a parameter?

Details

The extended GP model \insertCitenaveau2016modelingtcG is define for positive rainfall as

Y+ = ym + \sigma H_\xi^{-1}(U^{1/\alpha}),

with H_\xi the cdf of a GPD.

Value

A list of four elements containing the results of the fitted model. par gives the fitted parameters. AIC gives the Akaike criterion. fit.boot gives the parameters fitted with the bootstrap replicates. Finally for.plots is a list that is used by the function res.plot.

References

\insertAllCited

Examples

## Not run: 
res2=extGP.fit(rain[rain>0], c(2,.5,.5), ym=.3, step=.1, R=50)

## End(Not run)

mbtgy/tcG documentation built on Oct. 19, 2023, 3:10 p.m.