R: Additional Bootstrap Functions for Univariate EVA

xbooter {extRemes} | R Documentation

## Additional Bootstrap Functions for Univariate EVA

### Description

Additonal bootstrap capabilities for extreme-value analysis for fevd objects.

### Usage

    xbooter(x, B, rsize, block.length = 1,
    	return.period = c(10, 20, 50, 100, 200, 500),
    	qcov = NULL, qcov.base = NULL, shuffle = NULL,
    	replace = TRUE, verbose = FALSE, ...)

### Arguments

`x` | list object of class “fevd”
`B, rsize, block.length, shuffle, replace` | See the help file for booter from the distillery package.
`return.period` | numeric value for the desired return period for which CIs are desired.
`qcov` | numeric matrix with rows the same length as `q` and columns equal to the number of parameters (+ 1 for the threshold, if a POT model). This gives any covariate values for a nonstationary model. If NULL, and model is non-stationary, only the intercept terms for modeled parameters are used, and if a non-constant threshold, only the first threshold value is used. Not used if model is stationary.
`qcov.base` | numeric matrix analogous to `qcov`. When provided, the function returns the difference in return levels between the level for the covariates in `qcov` and the level for covariates in `qcov.base`.
`verbose` | logical if TRUE progress information is printed to the screen.
`...` | Additonal optional arguments to the `booter` function.

### Details

The `ci` method function will perform parametric bootstrapping for “fevd” objects, but this function is a wrapper to `booter`, which allows for greater flexibility with “fevd” objects. Gives CIs for the EVD parameters and return levels.

### Value

Object of class “booted” is returned. See the help file for `booter` for more information.

### Author(s)

Eric Gilleland

### See Also

`fevd`, `booter`, `xtibber`, `ci.fevd`

### Examples

    set.seed( 409 )
    z <- apply( matrix( rnorm( 100 * 1000 ), 1000, 100 ), 2, max )
    fit <- fevd( z )

    # In order to keep the code fast for CRAN compiling,
    # a low value for B is used here, but should use a larger
    # value in general.
    bfit <- xbooter( fit, B = 50, verbose = TRUE )
    ci( bfit, type = "perc" )

[Package extRemes version 2.0-12 Index]