Maximum likelihood estimation for weighted generalized Pareto distribution

Weighted maximum likelihood estimation, with user-specified vector of weights.

Usage

fit.wgpd(xdat, threshold = 0, weightfun = Stein_weights, start = NULL, ...)

xdat: vector of observations
threshold: numeric, value of the threshold
weightfun: function whose first argument is the length of the weight vector
start: optional vector of scale and shape parameters for the optimization routine, defaults to NULL
...: additional arguments passed to the weighting function weightfun

a list with components

estimate a vector containing the scale and shape parameters (optimized and fixed).
std.err a vector containing the standard errors.
vcov the variance covariance matrix, obtained as the numerical inverse of the observed information matrix.
threshold the threshold.
method the method used to fit the parameter. See details.
nllh the negative log-likelihood evaluated at the parameter estimate.
nat number of points lying above the threshold.
pat proportion of points lying above the threshold.
convergence logical indicator of convergence.
weights vector of weights for exceedances.
exceedances excess over the threshold, sorted in decreasing order.