.fit.gpd.rob: 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)
Value
a list with the same components as fit.gpd,
in addition to
estimate: optimal bias-robust estimates of the scale and shape parameters.
weights: vector of OBRE weights.
Arguments
dat
a numeric vector of data
thresh
threshold parameter
k
bound on the influence function; the constant k is a robustness parameter
(higher bounds are more efficient, low bounds are more robust). Default to 4.
tol
numerical tolerance for OBRE weights iterations.
show
logical: should diagnostics and estimates be printed. Default to FALSE.
References
Dupuis, D.J. (1998). Exceedances over High Thresholds: A Guide to Threshold Selection,
Extremes, 1(3), 251--261.