ercv (version 1.0.1)

thrselect: Threshold selection algorithm

Description

Threshold selection algorithm.

Usage

thrselect(data, threshold=NA, nextremes=NA, omit=16, evi=NA, m=10, nsim=100, 
          conf.level=0.90, oprint=TRUE)

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.

conf.level

confidence level of the interval.

oprint

logical. If TRUE (default), the single solution is printed. In any case, the full solution is the output of the function.

Value

A list including two data.frame (solution and options). Each of the data.frame contains the following columns:

• m number of thresholds for testing tail index.

• nextremes number of thresholds for testing tail index.

• threshold the threshold value

• rcv residual coefficient of variation for selected threshold.

• 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.

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, Tm

Examples

# NOT RUN {
data("nidd.thresh", package = "evir")
thrselect(nidd.thresh, nsim=500)
# }