From: Tim Hesterberg <TimHesterberg_at_gmail.com>

Date: Mon, 28 Jul 2008 04:13:28 +0200

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https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Mon 28 Jul 2008 - 02:16:49 GMT

Date: Mon, 28 Jul 2008 04:13:28 +0200

I'll address the question of whether you can use the bootstrap to improve estimates, and whether you can use the bootstrap to "virtually increase the size of the sample".

Short answer - no, with some exceptions (bumping / Random Forests).

Tim Hesterberg

>Hi Doran,

*>
**>Maybe I am wrong, but I think bootstrap is a general resampling method which
**>can be used for different purposes...Usually it works well when you do not
**>have a presentative sample set (maybe with limited number of samples).
**>Therefore, I am positive with Michal...
**>
**>P.S., overfitting, in my opinion, is used to depict when you got a model
**>which is quite specific for the training dataset but cannot be generalized
**>with new samples......
**>
**>Thanks,
**>
**>--Jerry
**>2008/7/21 Doran, Harold <HDoran_at_air.org>:
**>
**>> > I used bootstrap to virtually increase the size of my
**>> > dataset, it should result in estimates more close to that
**>> > from the population - isn't it the purpose of bootstrap?
**>>
**>> No, not really. The bootstrap is a resampling method for variance
**>> estimation. It is often used when there is not an easy way, or a closed
**>> form expression, for estimating the sampling variance of a statistic.
*

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