Tm: Multiple threshold test for a GPD

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/Tm.R

Description

Multiple threshold test for a GPD.

Usage

1
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:

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

1
2
data("nidd.thresh",package = "evir")
Tm(nidd.thresh,evi=0, nextremes = 75)

Example output

 nextremes cvopt evi       tms pvalue
        75     1   0 0.9813543   0.24

ercv documentation built on Oct. 30, 2019, 9:49 a.m.