rlarg.diag: Diagnostic Plots for Order Statistics Models

In ismev: An Introduction to Statistical Modeling of Extreme Values

Description

Produces diagnostic plots for order statistics models using the output of the function rlarg.fit.

Usage

rlarg.diag(z, n = z$r)

Arguments

z	An object returned by rlarg.fit.
n	Probability and quantile plots are produced for the largest n order statistics.

Value

For stationary models four plots are initially produced; a probability plot, a quantile plot, a return level plot and a histogram of data with fitted density. Then probability and quantile plots are produced for the largest n order statistics.

For non-stationary models residual probability plots and residual quantile plots are produced for the largest n order statistics.

See Also

rlarg.fit

Examples

## Not run: data(venice)
## Not run: venfit <- rlarg.fit(venice[,-1])
## Not run: rlarg.diag(venfit)

Example output

Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-25. For overview type 'help("mgcv-package")'.

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