Efron Bradley
Stanford University, Stanford, California 94305, USA.
J Biopharm Stat. 2011 Nov;21(6):1052-62. doi: 10.1080/10543406.2011.607736.
This note concerns the use of parametric bootstrap sampling to carry out Bayesian inference calculations. This is only possible in a subset of those problems amenable to Markov-Chain Monte Carlo (MCMC) analysis, but when feasible the bootstrap approach offers both computational and theoretical advantages. The discussion here is in terms of a simple example, with no attempt at a general analysis.
本笔记涉及使用参数自助抽样来进行贝叶斯推断计算。这仅在适合马尔可夫链蒙特卡罗（MCMC）分析的问题子集中可行，但在可行时，自助抽样方法具有计算和理论优势。这里的讨论基于一个简单示例，并非试图进行一般性分析。
