Test-inversion bootstrap (TIB) for fevd class objects.
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, ...)
List object of class “fevd”.
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.
number or character stating which return level or which parameter to find CIs for.
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.
character naming the nuisance parameter.
See the help file for booter
from the distillery package for more information on these arguments.
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.
numeric between zero and one giving the desired confidence level.
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.
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
.
logical if TRUE will calculate Studentized intervals (generally not profitable with the TIB method).
Used with the RM method only. Numeric giving the size of increments to use in the root-finding algorithm.
Used with the RM method only. Numeric stating how close to the desired level of confidence is satisfactory.
numeric giving the maximum number of iterations for the root-finding algorithm before giving up.
logical, should all of the values in the root-finding search be kept? Needed if a plot will be made.
logical, if TRUE will print progress information to the screen.
optional arguments to nlminb
.
See the help file for tibber for more information on the value
This function provides a wrapper to the tibber
function from distillery for “fevd” objects.
Gilleland, E. (2020) Bootstrap methods for statistical inference. Part I: Comparative forecast verification for continuous variables. Journal of Atmospheric and Oceanic Technology, 37 (11), 2117 - 2134, doi: 10.1175/JTECH-D-20-0069.1.
Gilleland, E. (2020) Bootstrap methods for statistical inference. Part II: Extreme-value analysis. Journal of Atmospheric and Oceanic Technology, 37 (11), 2135 - 2144, doi: 10.1175/JTECH-D-20-0070.1.
# 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 )
# }
Run the code above in your browser using DataLab