Fisher Based Confidence Interval for the GP Distribution
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)
object |
|
prob |
The probability of non exceedance. |
conf |
Numeric. The confidence level. |
Returns a vector of the lower and upper bound for the confidence interval.
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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