Tm {ercv}

Multiple threshold test for a GPD

Description

Multiple threshold test for a GPD.

Usage

Tm(data, threshold = NA, nextremes = NA, omit = 16, evi = NA, m = 10, nsim = 100)

Arguments

data

a numeric vector.

threshold

a threshold value (either this or nextremes must be given but not both).

nextremes

the number of upper extremes to be used (either this or threshold must be given but not both).

omit

the minimum required number of upper extremes for computing residual statistics.

evi

extreme value index. In particular, the shape parammeter of a generalized Pareto distribution.

m

number of thresholds to do multiplicial test.

nsim

number of simulations.

Value

A data.frame containing the following columns:

• nextremes the number of upper extremes to be used.

• cvopt optimal coefficient of variation for the tail.

• evi the corresponding tail index for optimal coefficient of variation if evi parameter is NA.

• tms the statistic of the tail index test.

• pvalue p-value associated to tms.

Author(s)

Joan del Castillo, David Moriña Soler and Isabel Serra

References

del Castillo, J. and Padilla, M. (2016). Modeling extreme values by the residual coefficient of variation. SORT Statist. Oper. Res. Trans. 40(2), 303-320.

del Castillo, J. and Serra, I. (2015). Likelihood inference for Generalized Pareto Distribution. Computational Statistics and Data Analysis, 83, 116-128.

del Castillo, J., Daoudi, J. and Lockhart, R. (2014). Methods to Distinguish Between Polynomial and Exponential Tails. Scandinavian Journal of Statistics, 41, 382-393.

See Also

ercv-package, cievi, ccdfplot, cvevi, cvplot, evicv, fitpot, ppot, qpot, tdata, thrselect

Examples

data("nidd.thresh",package = "evir")
Tm(nidd.thresh,evi=0, nextremes = 75)