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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! …
Stochastic's user avatar
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 < …
Stochastic's user avatar
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 $B>1000$. …
Stochastic's user avatar