GPD_excess_probability: Tail excess probability prediction based on conditional GPD...

In EQRN: Extreme Quantile Regression Neural Networks for Risk Forecasting

Tail excess probability prediction based on conditional GPD parameters

Description

Tail excess probability prediction based on conditional GPD parameters

Usage

GPD_excess_probability(
  val,
  sigma,
  xi,
  interm_threshold,
  threshold_p,
  body_proba = "default",
  proba_type = c("excess", "cdf")
)

Arguments

val	Quantile value(s) used to estimate the conditional excess probability or cdf.
sigma	Value(s) for the GPD scale parameter.
xi	Value(s) for the GPD shape parameter.
interm_threshold	Intermediate (conditional) quantile(s) at level threshold_p used as a (varying) threshold.
threshold_p	Probability level of the intermediate conditional quantiles interm_threshold.
body_proba	Value to use when the predicted conditional probability is below threshold_p (in which case it cannot be precisely assessed by the model). If "default" is given (the default), paste0(">",1-threshold_p) is used if proba_type=="excess", and paste0("<",threshold_p) is used if proba_type=="cdf".
proba_type	Whether to return the "excess" probability over val (default) or the "cdf" at val.

Value

Vector of probabilities (and possibly a few body_proba values if val is not large enough) of the same length as the longest vector between val, sigma, xi and interm_threshold.

EQRN documentation built on April 4, 2025, 12:45 a.m.