# cvselect: Threshold selection via coefficient of variation In mev: Modelling of Extreme Values

 cvselect R Documentation

## Threshold selection via coefficient of variation

### Description

This function computes the empirical coefficient of variation and computes a weighted statistic comparing the squared distance with the theoretical coefficient variation corresponding to a specific shape parameter (estimated from the data using a moment estimator as the value minimizing the test statistic, or using maximum likelihood). The procedure stops if there are no more than 10 exceedances above the highest threshold

### Usage

``````cvselect(
xdat,
thresh,
method = c("mle", "wcv", "cv"),
nsim = 999L,
nthresh = 10L,
level = 0.05,
lazy = FALSE
)
``````

### Arguments

 `xdat` [vector] vector of observations `thresh` [vector] vector of threshold. If missing, set to `p^k` for `k=0` to `k=``nthresh` `method` [string], either moment estimator for the (weighted) coefficient of variation (`wcv` and `cv`) or maximum likelihood (`mle`) `nsim` [integer] number of bootstrap replications `nthresh` [integer] number of thresholds, if `thresh` is not supplied by the user `level` [numeric] probability level for sequential testing procedure `lazy` [logical] compute the bootstrap p-value until the test stops rejecting at level `level`? Default to `FALSE`

### Value

a list with elements

• `thresh`: value of threshold returned by the procedure, `NA` if the hypothesis is rejected at all thresholds

• `cthresh`: sorted vector of candidate thresholds

• `cindex`: index of selected threshold among `cthresh` or `NA` if none returned

• `pval`: bootstrap p-values, with `NA` if `lazy` and the p-value exceeds level at lower thresholds

• `shape`: shape parameter estimates

• `nexc`: number of exceedances of each threshold `cthresh`

• `method`: estimation method for the shape parameter

### References

del Castillo, J. and M. Padilla (2016). Modelling extreme values by the residual coefficient of variation, SORT, 40(2), pp. 303–320.

mev documentation built on May 29, 2024, 9:10 a.m.