Maximum likelihood estimation for weighted generalized Pareto distribution
Source:R/Stein.R
      fit.wgpd.RdWeighted maximum likelihood estimation, with user-specified vector of weights.
Arguments
- 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
Value
a list with components
- estimatea vector containing the- scaleand- shapeparameters (optimized and fixed).
- std.erra vector containing the standard errors.
- vcovthe variance covariance matrix, obtained as the numerical inverse of the observed information matrix.
- thresholdthe threshold.
- methodthe method used to fit the parameter. See details.
- nllhthe negative log-likelihood evaluated at the parameter- estimate.
- natnumber of points lying above the threshold.
- patproportion of points lying above the threshold.
- convergencelogical indicator of convergence.
- weightsvector of weights for exceedances.
- exceedancesexcess over the threshold, sorted in decreasing order.