Approximately Unbiased Bootstrap Vs Bootstrap
Hello everyone,
Can anyone give me a simple explanation of what an approximately unbiased bootstrap is with regards to hierarchical clustering? From what I read, it alters the sample size during randomization to calculate p-values. How is this approach better than the regular bootstrap which keeps the sample size intact while randomizing and also is it randomization with replacement?I'm confused. Please help!
Thanks!!!
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This sounds more like a question to be asked at CrossValidated (http://stats.stackexchange.com).
cross-posted here: http://stats.stackexchange.com/q/31739/183