extQuant: Extreme quantile estimation

In AntoineUC/Expectrem: Bias-reduced estimation of extreme value index and extreme quantiles, expectiles and Expected Shortfalls

Extreme quantile estimation

Description

This function computes the Weissman-type estimator for extreme quantiles.

Usage

extQuant(X, k="kopt", tau, estim = "Hill", br = FALSE)

Arguments

X	Data vector.
k	A vector of number of upper order statistics. Default: optimal k given in Girard et al. (2020).
tau	Numeric (extreme) probability with value in [0,1].
estim	Tail index estimator used : Hill estimator ("Hill", default) or proportionality estimator ("tindexp").
br	Bias reduced version if TRUE. Default: FALSE.

Author(s)

Antoine Usseglio-Carleve

References

Weissman, I. (1978). Estimation of parameters and large quantiles based on the k largest observations. Journal of the American Statistical Association, 73(364):812-815. Girard, S., Stupfler, G., and Usseglio-Carleve, A. (2020). On second-order automatic bias reduction for extreme expectile estimation, preprint.

AntoineUC/Expectrem documentation built on Feb. 14, 2025, 11:22 a.m.