fit.GPD {QRMlib} | R Documentation |
fits a generalized Pareto distribution to threshold exceedances
fit.GPD(data, threshold=NA, nextremes=NA, method="ml", information="observed")
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. |
see page 278 of QRM; this function uses optim() for ML
a list containing parameter estimates, standard errors and details of the fit
Parameter and quantile estimation for the generalized Pareto distribution, JRM Hosking and JR Wallis, Technometrics 29(3), pages 339-349, 1987.
data(danish); plot(danish); losses <- seriesData(danish); mod <- fit.GPD(danish,threshold=10); mod; modb <- fit.GPD(danish,threshold=10,method="pwm"); modb;