fit.GPD {QRMlib}R Documentation

Fit Generalized Pareto Model

Description

fits a generalized Pareto distribution to threshold exceedances

Usage

fit.GPD(data, threshold=NA, nextremes=NA, method="ml", information="observed")

Arguments

data data vector or times series
threshold a threshold value (either this or "nextremes" must be given but not both)
nextremes the number of upper extremes to be used (either this or "threshold" must be given but not both)
method whether parameters should be estimated by the maximum likelihood method "ml" or the probability-weighted moments method "pwm"
information whether standard errors should be calculated with "observed" or "expected" information. This only applies to maximum likelihood method; for "pwm" method "expected" information is used if possible.

Details

see page 278 of QRM; this function uses optim() for ML

Value

a list containing parameter estimates, standard errors and details of the fit

References

Parameter and quantile estimation for the generalized Pareto distribution, JRM Hosking and JR Wallis, Technometrics 29(3), pages 339-349, 1987.

See Also

pGPD, fit.GPDb, pGEV, fit.GEV

Examples

data(danish);
plot(danish); 
losses <- seriesData(danish); 
mod <- fit.GPD(danish,threshold=10); 
mod; 
modb <- fit.GPD(danish,threshold=10,method="pwm"); 
modb; 

[Package QRMlib version 1.4.4 Index]