fgpdset: Fit collection of GPD models to compounding exceedances as...

In gbstat/tailqr: 'Fit Mixture of Quantile Regression and GPDs'

Description

Fit collection of GPD models to compounding exceedances as defined in get_exceedances

Usage

fgpdset(excd.list, Xb, type = c("upper", "lower"), return.qs = FALSE,
  pred.taus = NULL, use.winter.shape = FALSE, all.winter.ind = NULL,
  Xb.pred.time = NULL)

Arguments

excd.list	list of exceedances created by get_exceedances
Xb	basis design matrix for tails (log(scale) of GPD). Each basis function is in a separate column.
type	one of "upper" or "lower" if fitting upper or lower tails
return.qs	(logical) should quantile estimates be returned
pred.taus	vector of quantiles to predict
use.winter.shape	(logical) should a separate shape parameter be estimated for the winter months?
all.winter.ind	indicator for which dates correspond to winter months
Xb.pred.time	Basis matrix for prediction dates.

Value

List of fitted parameter matrix (one column for each GPD order: log(scale), shape) and estimated quantiles (qs, of dimension time, taus, model).

gbstat/tailqr documentation built on May 8, 2019, 5:42 p.m.