plot.bvpot: Graphical Diagnostics: the Bivariate Extreme Value...

In POT: Generalized Pareto Distribution and Peaks Over Threshold

Graphical Diagnostics: the Bivariate Extreme Value Distribution Model.

Description

Plot several graphics to judge goodness of fit of the fitted model.

Usage

## S3 method for class 'bvpot'
plot(x, mains, which = 1:3, ask = nb.fig < length(which)
&& dev.interactive(), ...)

Arguments

x	An object of class "bvpot". Most often, the object returned by the fitbvgpd function.
mains	May be missing. If present a 3–vector of character strings which gives the titles of the plots.
which	a numeric vector which specifies which plot must be drawn : '1' for Pickands' Dependence Function plot, '2' for a bivariate return level plot, '3' for the spectral density plot.
ask	Logical. If TRUE, user is asked before each plot.
...	Other parameters to pass to the plot function.

Value

Several plots.

Author(s)

Mathieu Ribatet

See Also

fitbvgpd

Examples

x <- rbvgpd(1000, alpha = 0.55, mar1 = c(0,1,0.25), mar2 = c(2,0.5,0.1))
Mlog <- fitbvgpd(x, c(0, 2), "log")
layout(matrix(c(1,1,2,2,0,3,3,0), 2, byrow = TRUE))
plot(Mlog)

POT documentation built on Oct. 17, 2024, 5:06 p.m.