Compute Fisher based confidence intervals on parameter and return level for the GP distribution. This is achieved through asymptotic theory and the Observed information matrix of Fisher and eventually the Delta method.
gpd.fishape(object, conf = 0.95)
gpd.fiscale(object, conf = 0.95)
gpd.firl(object, prob, conf = 0.95)Returns a vector of the lower and upper bound for the confidence interval.
R object given by function fitgpd.
The probability of non exceedance.
Numeric. The confidence level.
Mathieu Ribatet
rp2prob, prob2rp,
gpd.pfscale,
gpd.pfshape, gpd.pfrl and
confint
data(ardieres)
ardieres <- clust(ardieres, 4, 10 / 365, clust.max = TRUE)
f1 <- fitgpd(ardieres[,"obs"], 5, 'mle')
gpd.fishape(f1)
gpd.fiscale(f1)
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