extRemes (version 2.1-3)

bvpotbooter: Bootstrap Functions for Bivariate POT

Description

Obtains bootstrap samples for the bivariate POT model as output from fbvpot.

Usage

bvpotbooter(object, B, rsize, block.length = 1, shuffle = NULL, replace = TRUE, ...)

Value

A list object of class “booted”.

call

the function call

data

original data series

statistic, B, block.length, replace, rsize

same arguments as passed in

results

B column matrix giving the paramter estimates for each bootstrap resample.

type

character stating whether the resample method is iid or cbb.

Arguments

object

A list object of class “fbvpot”.

B

integer giving the number of bootstrap resamples to obtain.

rsize

integer giving the size of the bootstrap samples. Defaults to the (original) sample size. For heavy-tailed data, may want to use a smaller size (e.g., square root of the original sample size).

block.length

integer giving the length of blocks to use (for dependent data). Default is unity, which yields IID samples.

shuffle

(optional) rsize by B matrix giving the indices for the bootstrap resamples. If provided, B may be missing.

replace

logical, should the resamples be taken with replacement?

...

Not used.

Author

Eric Gilleland

Details

Performs bootstrap resampling for bivariate POT inference. CI's are obtained by calling the ci function. See the help file for booter from the distillery package for more details.

See Also

fbvpot, booter, ci

Examples

if (FALSE) {
data( "SantaAna" )

Z <- SantaAna[,3:4]

mfit1 <- fevd( x = temp, data = Z, threshold = 36.75, type = "GP" )
mfit2 <- fevd( x = windspeeds, data = Z, threshold = 7.09875, type = "GP" )

fit2 <- fbvpot( x = Z, threshold = apply( Z, 2, quantile, probs = 0.95 ),
	                      tform = "tf", fit = list( mfit1, mfit2 ) )

# Note, using B = 50 below for R check speed, but probably need
# a higher number.
fit2booted <- bvpotbooter( fit2, B = 50, rsize = 62, block.length = 7 )
summary( fit2booted )
ci( fit2booted, type = "perc" )
}