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hill

Hill estimator


Description

Compute the weighted Hill estimator.

Usage

hill(X, weights = rep(1, length(X)), grid = X)

Arguments

X

a vector of data.

weights

a vector of weights assiociated to x.

grid

a vector of values for which the Hill estimator is computed.

Details

Compute the weighted Hill estimator for vectors grid, data and weights (see references below).

Value

xsort

the sorted data.

wsort

the weights assiociated to xsort.

grid

the grid for which the Hill estimator is computed.

hill

the Hill estimators.

Author(s)

Ion Grama

References

Grama, I. and Spokoiny, V. (2008). Statistics of extremes by oracle estimation. Ann. of Statist., 36, 1619-1648.

Durrieu, G. and Grama, I. and Pham, Q. and Tricot, J.- M (2015). Nonparametric adaptive estimator of extreme conditional tail probabilities quantiles. Extremes, 18, 437-478.

Hill, B.M. (1975). A simple general approach to inference about the tail of a distribution. Annals of Statistics, 3, 1163-1174.

Examples

X <- abs(rcauchy(100))
weights <- rep(1, length(X))
wh <- hill(X, w = weights)

extremefit

Estimation of Extreme Conditional Quantiles and Probabilities

v1.0.2
GPL-2
Authors
Gilles Durrieu, Ion Grama, Kevin Jaunatre, Quang-Khoai Pham, Jean-Marie Tricot
Initial release
2019-05-03

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