R: Test-Inversion Bootstrap for Extreme-Value Analysis

xtibber {extRemes}

R Documentation

Test-Inversion Bootstrap for Extreme-Value Analysis

Description

Test-inversion bootstrap (TIB) for fevd class objects.

Usage

xtibber(x, type = c("return.level", "parameter"), which.one,
	tib.method = c("interp", "rm"), nuisance = "shape", B,
	test.pars, rsize, block.length = 1, shuffle = NULL,
	replace = TRUE, alpha = 0.05, qcov = NULL,
	qcov.base = NULL, stud = FALSE, step.size, tol = 1e-04,
	max.iter = 1000, keep.iters = TRUE, verbose = FALSE, ...)

Arguments

`x`	List object of class “fevd”.
`type`	character string stating whether to calculate TIB intervals for a return level or a parameter as this funciton will only calculate an interval for a single parameter/return level at a time.
`which.one`	number or character stating which return level or which parameter to find CIs for.
`tib.method`	character stating whether to estimate the TIB interval by interpolating from a series of pre-determined values of the nuisance parameter or to use the Robbins-Monroe (RM) method. See the help file for `tibber` from the distillery package for more information.
`nuisance`	character naming the nuisance parameter.
`B, rsize, block.length, shuffle, replace`	See the help file for `booter` from the distillery package for more information on these arguments.
`test.pars`	numeric vector giving the sequence of nuisance parameter values for the interpolation method, or a numeric vector of length two giving the starting values for the RM method.
`alpha`	numeric between zero and one giving the desired confidence level.
`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`.
`stud`	logical if TRUE will calculate Studentized intervals (generally not profitable with the TIB method).
`step.size`	Used with the RM method only. Numeric giving the size of increments to use in the root-finding algorithm.
`tol`	Used with the RM method only. Numeric stating how close to the desired level of confidence is satisfactory.
`max.iter`	numeric giving the maximum number of iterations for the root-finding algorithm before giving up.
`keep.iters`	logical, should all of the values in the root-finding search be kept? Needed if a plot will be made.
`verbose`	logical, if TRUE will print progress information to the screen.
`...`	optional arguments to `nlminb`.

Details

This function provides a wrapper to the tibber function from distillery for “fevd” objects.

Value

See the help file for tibber for more information on the value

Author(s)

Eric Gilleland

Examples

## Not run: 
data("ftcanmax")
fit <- fevd( Prec, data = ftcanmax )

tbfit <- xtibber( fit, which.one = 100, B = 500,
		 test.pars = seq(-0.01,0.2,,100), verbose = TRUE )

tbfit

plot( tbfit )


## End(Not run)

[Package extRemes version 2.0-12 Index]