I am looking for any recommendations on resources to learn more about bootstrapping from a theoretical and rigorous perspective in terms of bounds/guarantees/etc. Any books or papers would be very much appreciated!
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Do you mean besides the recommendations at https://stats.stackexchange.com/questions/128839 and https://stats.stackexchange.com/questions/6538? – whuber Aug 09 '22 at 14:26
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Yep, besides those. I think I am more interested in learning how it applies to statistical learning theory - especially to something like random forests and when your draws may not be i.i.d – Nicolas Beltran Aug 10 '22 at 09:47
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Thank you -- please include that in your question so that the answers here don't duplicate the answers in the other threads. – whuber Aug 10 '22 at 13:36
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Bradley Efron is the statistician that introduced the bootstrap sampling technique. His original paper is Bootstrap Methods: Another Look at the Jacknife.
Efron also released Computer Age Statistical Inference with Trevor Hastie in 2016 which has a chapter on the Jackknife and the Bootstrap. The book is available for download on the linked site above.
Larry Wasserman's All of Statistics: A Concise Course in Statistical Inference has a great chapter on the bootstrap as well but I don't believe this book has been made freely available.
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