gpd.prof: Profile Log-likelihoods for Stationary GPD Models

Description Usage Arguments Value See Also Examples

Description

Produce profile log-likelihoods for shape parameters and m year/block return levels for stationary GPD models using the output of the function gpd.fit.

Usage

1
2
gpd.prof(z, m, xlow, xup, npy = 365, conf = 0.95, nint = 100)
gpd.profxi(z, xlow, xup, conf = 0.95, nint = 100)

Arguments

z

An object returned by gpd.fit. The object should represent a stationary model.

m

The return level (i.e.\ the profile likelihood is for the value that is exceeded with probability 1/m).

xlow, xup

The least and greatest value at which to evaluate the profile likelihood.

npy

The number of observations per year.

conf

The confidence coefficient of the plotted profile confidence interval.

nint

The number of points at which the profile likelihood is evaluated.

Value

A plot of the profile likelihood is produced, with a horizontal line representing a profile confidence interval with confidence coefficient conf.

See Also

gpd.fit, gpd.diag

Examples

1
2
3
4
data(rain)
rnfit <- gpd.fit(rain, 10)
## Not run: gpd.prof(rnfit, m = 10, 55, 75)
## Not run: gpd.profxi(rnfit, -0.02, 0.15)

Example output

Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-28. For overview type 'help("mgcv-package")'.
$threshold
[1] 10

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 6123.465

$mle
[1] 7.43768624 0.05045225

$rate
[1] 0.1142547

$se
[1] 0.23606472 0.02256649

ismev documentation built on May 1, 2019, 9:10 p.m.

Related to gpd.prof in ismev...