gpdRangeFit: Estimate generalized Pareto distribution parameters over a...

In texmex: Threshold exceedences and multivariate extremes

Description

Estimate generalized Pareto distribution parameters over a range of values, using maximum (penalized) likelihood.

Usage

gpdRangeFit(data, umin=quantile(data, .05), umax=quantile(data, .95), nint = 10, 
            penalty = "gaussian", priorParameters = NULL, alpha=0.05,
            xlab = "Threshold", ylab = NULL, main = NULL, addNexcesses=TRUE, ...)

Arguments

data	The data vector to be modelled.
umin	The minimum threshold above which to esimate the parameters.
umax	The maximum threshold above which to esimate the parameters.
nint	The number of thresholds at which to perform the estimation.
penalty	The type of penalty to be used in the maximum penalized likelihood estimation. Should be either “gaussian” or “none”. Defaults to “gaussian”.
priorParameters	Parameters to be used for the penalty function. See the help for gpd for more informaiton.
alpha	(1 - alpha)% confidence intervals will be plotted with the point estimates. Defaults to alpha = 0.05.
xlab	Label for the x-axis.
ylab	Label for the y-axis.
main	The main title.
addNexcesses	Annotate top axis with numbers of threshold excesses arising with the corresponding values of threshold on the bottom axis.
...	Arguments to plot

Details

This is Stuart Coles' gpd.fitrange, as it appears in the ismev package, with some fairly minor changes. The function uses gpd internally and uses the default options for that function.

Note this function does not extend to assessing model fit when there are covariates included in the mdoel.

Author(s)

Stuart Coles, Janet E Heffernan, Harry Southworth

See Also

gpd

Examples

par(mfrow=c(1,2))
gpdRangeFit(rain)

Example output

Loading required package: mvtnorm
Loading required package: ggplot2

Scale parameter
---------------
      threshold      phi        lo       hi
 [1,]  0.000000 1.746263 1.7148245 1.777702
 [2,]  1.833333 1.664680 1.5842499 1.745109
 [3,]  3.666667 1.543931 1.3939124 1.693949
 [4,]  5.500000 1.671849 1.4514755 1.892222
 [5,]  7.333333 1.462617 1.1348385 1.790396
 [6,]  9.166667 1.850673 1.4523096 2.249036
 [7,] 11.000000 1.510240 0.9511203 2.069359
 [8,] 12.833333 1.679563 0.9935579 2.365568
 [9,] 14.666667 1.146136 0.2310322 2.061240
[10,] 16.500000 1.421912 0.3409299 2.502894

Shape parameter
---------------
      threshold         xi            lo         hi
 [1,]  0.000000 0.12724094  1.031277e-01 0.15135416
 [2,]  1.833333 0.09744960  6.983946e-02 0.12505974
 [3,]  3.666667 0.09182598  5.982390e-02 0.12382806
 [4,]  5.500000 0.05452630  2.074989e-02 0.08830271
 [5,]  7.333333 0.06754958  2.820090e-02 0.10689826
 [6,]  9.166667 0.02295371 -1.610288e-02 0.06201030
 [7,] 11.000000 0.04653099 -7.229458e-05 0.09313428
 [8,] 12.833333 0.03033252 -1.922972e-02 0.07989476
 [9,] 14.666667 0.05911131  6.006673e-04 0.11762196
[10,] 16.500000 0.03937115 -2.244013e-02 0.10118242

texmex documentation built on May 2, 2019, 4:56 p.m.