PORT.Hill: Peaks over random threshold Hill estimate

PORT.HillR Documentation

Peaks over random threshold Hill estimate

Description

This function performs peaks over random threshold (PORT) Hill methodology for estimating extreme value index (EVI) for heavy tailed models.

Usage

PORT.Hill(x, k, q, method = c("PMOP", "PRBMOP"))

Arguments

x

Data vector.

k

a vector of number of upper order statistics.

q

quantile for PORT.

method

Method used, ("PMOP", default) and reduced-bias PMOP ("PRBMOP").

Details

The computation of PORT Hill estimator is based on the work by Araujo Santos et al. (2006). Reduced biased PORT Hill computation is based on quasi-PORT methodology, see Gomes et al.

Value

a k dimensional vector of PORT Hill estimates. When Method = "RBMOP" shape and scale second order parameters estimates are also returned.

Author(s)

B G Manjunath bgmanjunath@gmail.com, Frederico Caeiro fac@fct.unl.pt

References

Araujo Santos, P., Fraga Alves, M.I. and Gomes, M.I. (2006). Peaks over random threshold methodology for tail index and quantile estimation. Revstat, 4(3), 227–247.

Gomes, M.I., Figueiredo, F., Henriques-Rodrigues, L. and Miranda, M.C. (2006). A quasi-PORT methodology for VaR based on second-order reduced-bias estimation.

Examples

# generate random samples               
x = rfrechet(50000, loc = 0, scale = 1,shape = 1/0.5)

# estimate PORT Hill 
PORT.Hill(x,c(1,500,5000),0.1,"PRBMOP")

evt0 documentation built on April 22, 2023, 1:15 a.m.