.fit.gpd.rob {mev} | R Documentation |
Robust threshold selection of Dupuis
Description
The optimal bias-robust estimator (OBRE) for the generalized Pareto. This function returns robust estimates and the associated weights.
Usage
.fit.gpd.rob(dat, thresh, k = 4, tol = 1e-05, show = FALSE)
Arguments
dat |
a numeric vector of data |
thresh |
threshold parameter |
k |
bound on the influence function; the constant |
tol |
numerical tolerance for OBRE weights iterations. |
show |
logical: should diagnostics and estimates be printed. Default to |
Value
a list with the same components as fit.gpd
,
in addition to
-
estimate
: optimal bias-robust estimates of thescale
andshape
parameters. -
weights
: vector of OBRE weights.
References
Dupuis, D.J. (1998). Exceedances over High Thresholds: A Guide to Threshold Selection, Extremes, 1(3), 251–261.
See Also
Examples
dat <- rexp(100)
.fit.gpd.rob(dat, 0.1)
[Package mev version 1.17 Index]