Bootstrap估计及其应用

Bootstrap Estimation And Its Applications

本文介绍了一种面向应用的、基于大量计算的统计推断——ｂｏｏｔｓｔｒａｐ法。它是以原始数据为基础的模拟抽样统计推断法，用于研究原始数据的某统计量的分布特征，特别适用于那些难以用常规方法导出的参数的区间估计、假设检验等问题。讨论了参数与非参数的ｂｏｏｔｓｔｒａｐ法，ｂｏｏｔｓｔｒａｐ的估计误差，ｂｏｏｔｓｔｒａｐ与ＭｏｎｔｅＣａｒｌｏ模拟的区别，ｊａｃｋｎｉｆｅ与ｂｏｏｔｓｔｒａｐ的联合估计等问题。

Bootstrap, a new statistical inference methodolgy,was introduced and illustrated in the practical business.It is data based simulation to carry out familiar statistical calculations,such as standard error,biases,confidence intervals,et al. in a unfamiliar way: by purely computation means rather than using of statistical formulas.It is useful especially when the statistical formulas are hard to be got. Both parametric bootstrap and non parametric bootstrap,the estimated error of bootstrap, the distinction of bootstrap and Monte Carlo simulation, bootstrap after jacknife are discussed.