著名统计学家Peter Hall 在浙大暑期班的讲义

共125页 内容：

1. Bootstrap principle: definition; history;
examples of problems that can be solved; different
versions of the bootstrap
2. Explaining the bootstrap in theoretical
terms: introduction to (Chebyshev-)Edgeworth
approximations to distributions; rigorous
development of Edgeworth expansions;
‘smooth function model’; Edgeworth-based
explanations for the bootstrap

3. Bootstrap iteration: principle and theory
4. Bootstrap in non-regular cases: Difficulties
that the bootstrap has modelling extremes;
m-out-of-n bootstrap; bootstrap for
curve estimation
5. Bootstrap for time series: ‘structural’
and ‘non-structural’ implementations; block
bootstrap methods
6. Speeding the performance of Monte
Carlo simulation

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