POT: profconf – R documentation

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profconf

Profiled Confidence interval for the GP Distribution

Description

Compute profiled confidence intervals on parameter and return level for the GP distribution. This is achieved through the profile likelihood procedure.

Usage

gpd.pfshape(object, range, xlab, ylab, conf = 0.95, nrang = 100,
vert.lines = TRUE, ...)
gpd.pfscale(object, range, xlab, ylab, conf = 0.95, nrang = 100,
vert.lines = TRUE, ...)
gpd.pfrl(object, prob, range, thresh, xlab, ylab, conf = 0.95, nrang =
100, vert.lines = TRUE, ...)

Arguments

`object`	`R` object given by function `fitgpd`.
`prob`	The probability of non exceedance.
`range`	Vector of dimension two. It gives the lower and upper bound on which the profile likelihood is performed.
`thresh`	Optional. The threshold. Only needed with non constant threshold.
`xlab, ylab`	Optional Strings. Allows to label the x-axis and y-axis. If missing, default value are considered.
`conf`	Numeric. The confidence level.
`nrang`	Numeric. It specifies the number of profile likelihood computed on the whole range `range`.
`vert.lines`	Logical. If `TRUE` (the default), vertical lines are plotted.
`...`	Optional parameters to be passed to the `plot` function.

Value

Returns a vector of the lower and upper bound for the profile confidence interval. Moreover, a graphic of the profile likelihood function is displayed.

Author(s)

Mathieu Ribatet

References

Coles, S. (2001). An Introduction to Statistical Modelling of Extreme Values. Springer Series in Statistics. London.

Examples

data(ardieres)
events <- clust(ardieres, u = 4, tim.cond = 8 / 365,
clust.max = TRUE)
MLE <- fitgpd(events[, "obs"], 4, 'mle')
gpd.pfshape(MLE, c(0, 0.8))
rp2prob(10, 2)
gpd.pfrl(MLE, 0.95, c(12, 25))

POT

Generalized Pareto Distribution and Peaks Over Threshold

v1.1-10

GPL (>= 2)

Authors

Mathieu Ribatet [aut], Christophe Dutang [ctb,cre]

Initial release