<P>著名统计学家Peter Hall 在浙大暑期班的讲义</P>
<P>共125页 内容：</P>
<P>1. Bootstrap principle: definition; history;<BR>examples of problems that can be solved; different<BR>versions of the bootstrap<BR>2. Explaining the bootstrap in theoretical<BR>terms: introduction to (Chebyshev-)Edgeworth<BR>approximations to distributions; rigorous<BR>development of Edgeworth expansions;<BR>‘smooth function model’; Edgeworth-based<BR>explanations for the bootstrap</P>
<P>3. Bootstrap iteration: principle and theory<BR>4. Bootstrap in non-regular cases: Difficulties<BR>that the bootstrap has modelling extremes;<BR>m-out-of-n bootstrap; bootstrap for<BR>curve estimation<BR>5. Bootstrap for time series: ‘structural’<BR>and ‘non-structural’ implementations; block<BR>bootstrap methods<BR>6. Speeding the performance of Monte<BR>Carlo simulation</P><BR>