tboot_dist {boodd} | R Documentation |
Computation of the Bootstrap-t Distribution
Description
Computes and plots the bootstrap-t distribution of a statistic when an estimator of the variance is available.
Usage
tboot_dist(
boot_obj,
comp = 1,
PLT = TRUE,
nn = TRUE,
recenter = FALSE,
return_values = FALSE,
...
)
Arguments
boot_obj |
A |
comp |
The index of the component of the statistic to be plotted. |
PLT |
Logical. If |
nn |
Logical. If |
recenter |
Logical. If |
return_values |
Logical. If |
... |
Additional arguments affecting the plot produced (e.g., nclass, main, ylim,...). |
Details
The tboot_dist
function is designed to work with bootstrap samples that
include estimates of both the parameters of interest and their variances.
The function calculates a studentized version of the bootstrap distribution
(the bootstrap-t distribution) and optionally plots this distribution and the normal
approximation.
Value
Optionally returns a numeric vector representing the bootstrap-t distribution of the selected component.
References
Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted.
Efron, B., Tibshirani, R. (1993). An Introduction to the Bootstrap, Chapman and Hall.
See Also
boots
, class.boodd
, jackVar
,
confint.boodd
.
Examples
set.seed(5)
m=0
n=100
X=rnorm(n,mean=m)
mv=function(X){
c(mean(X), var(X)/length(X))}
# the function mv computes the estimates of the mean and variance of the mean
resb=boots(X,mv,B=999)
# compare distributions
tboot_dist(resb,1)