texmex (version 1.1)

gpdRangeFit: Estimate generalized Pareto distribution parameters over a range of values

Description

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

Usage

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

Arguments

data

The data vector to be modelled.

umin

The minimum threshold to esimate the parameters over.

umax

The maximum threshold to esimate the parameters over.

nint

The number of points 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.

...

Arguments to plot

Details

This is Stuart Coles's 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.

See Also

gpd