pp.diag: Diagnostic Plots for Point Process Models

In ismev: An Introduction to Statistical Modeling of Extreme Values

Description

Produces diagnostic plots for point process models using the output of the function pp.fit.

Usage

pp.diag(z)

Arguments

z	An object returned by pp.fit.

Value

For stationary models two plots are produced; a probability plot and a quantile plot.

For non-stationary models two plots are produced; a residual probability plot and a residual quantile plot.

See Also

pp.fit, gpd.fit

Examples

data(rain)
rnfit <- pp.fit(rain, 10)
pp.diag(rnfit)

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

$npy
[1] 365

$nexc
[1] 2003

$conv
[1] 0

$nllh
[1] 654.1282

$mle
[1] 40.55755732  8.99195409  0.05088103

$se
[1] 1.00078098 0.60031529 0.02247418

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