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The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
3
votes
3
answers
414
views
Data generating process for non-parametric bootstrap
Can anyone give an explanation of the data generating process for the non-parametric bootstrap? … Bootstrap is often used when the sample size is fairly small, lets say n < 15, but it fails mostly when n < 5.
Thanks a lot! …
6
votes
Accepted
How to estimate the acceleration term used in boot.ci()
In the code below is an example where I uses the patch data in the bootstrap library. I calculated the BC$_a$ interval manually. … The above mentioned notes also have examples with implementation in R.
library(bootstrap)
library(boot)
# Functions for the bootstrap and confidence interval
theta.func <- function(x){
y.val < …
1
vote
Bootstrap stats question regarding how many replicates need to ran to see a difference
I cannot really help you in python, but for choosing the number of replications ($B$), you can calculate the ideal bootstrap. … Back in 1993, Efron and Tibshirani in An introduction to the bootstrap suggested $B=200$ for the standard error. As for confidence intervals, they suggested $B>1000$. …