xbooter | R Documentation |
Additonal bootstrap capabilities for extreme-value analysis for fevd objects.
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, ...)
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 |
qcov.base |
numeric matrix analogous to |
verbose |
logical if TRUE progress information is printed to the screen. |
... |
Additonal optional arguments to the |
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.
Object of class “booted” is returned. See the help file for booter
for more information.
Eric Gilleland
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.
fevd
, booter
, xtibber
, ci.fevd
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" )
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