Fit the GP Distribution {RFA}R Documentation

Fitting a POT model through a GP distribution

Description

Maximum Likelihood, Unbiased Probability Weigthed Moments, Biased Probability Weighted Moments and Moments Estimator to fit Peaks Over a Threshold to a GP distribution.

Usage

fitgpd(data, threshold, method, ...)

Arguments

data A numeric vector.
threshold A numeric value giving the threshold for the GPD
method A string giving the names of the estimator. It can be 'mle', 'moments', 'pwmu' and 'pwmb' for the maximum likelihood, moments, unbiased probability weighted moments, biased probability weigthed moments estimators respectively.
... Other optional arguments to be passed to gpdmoments, gpdpwmu, gpdpwmb and gpdmle functions.

Value

This function returns a list with composants:

estimate A vector containing the maximum likelihood estimates.
std.err A vector containing the standard errors.
fixed A vector containing the parameters of the model that have been held fixed.
param A vector containing all parameters (optimized and fixed).
deviance The deviance at the maximum likelihood estimates.
corr The correlation matrix - for the mle method.
convergence, counts, message Components taken from the list returned by optim - for the mle method.
threshold The threshold passed to argument threshold.
nhigh The number of exceedences.
nat, pat The number and proportion of exceedences.
data The data passed to the argument data.
exceedances The exceedences, or the maxima of the clusters of exceedences.
scale The scale parameter for the fitted generalized Pareto distribution.
call The call of the current function.

Note

The Maximum Likelihood estimator is obtained through a sligthly modified version of Alec Stephenson's fpot.norm function in the evd package.


[Package RFA version 0.0-8 Index]