maxbootr {maxbootR} | R Documentation |
Bootstrap Estimation for Block Maxima
Description
Performs bootstrap resampling for various block maxima estimators (mean, variance, GEV parameters, quantile, return level) using either disjoint or sliding block methods.
Usage
maxbootr(
xx,
est,
block_size,
B = 1000,
type = "sb",
seed = 1,
p = NULL,
annuity = NULL
)
Arguments
xx |
A numeric vector or array containing univariate samples. For multivariate cases, samples should be arranged in rows. |
est |
A string specifying the estimator to apply. Must be one of |
block_size |
Integer. Size of each block used in the block maxima extraction. |
B |
Integer. Number of bootstrap replicates to generate. |
type |
Type of block bootstrapping: |
seed |
Integer. Seed for reproducibility. |
p |
Optional numeric value in (0,1). Required if |
annuity |
Optional numeric value > 1. Required if |
Value
A numeric vector with B
rows for scalar estimators. If est = "gev"
, a matrix with B
rows is returned. Each row contains 3 estimated GEV parameters (location, scale, shape).
Examples
if (requireNamespace("maxbootR", quietly = TRUE)) {
library(maxbootR)
set.seed(123)
x <- rnorm(100)
# Bootstrap mean using sliding blocks
boot_mean <- maxbootr(x, est = "mean", block_size = 10, B = 20, type = "sb")
# Bootstrap variance using disjoint blocks
boot_var <- maxbootr(x, est = "var", block_size = 10, B = 20, type = "db")
# Bootstrap 95%-quantile of block maxima using sliding blocks
boot_q <- maxbootr(x, est = "quantile", block_size = 10, B = 20, type = "db", p = 0.95)
}