BAYESIAN STATISTICS WITHOUT TEARS - A SAMPLING RESAMPLING PERSPECTIVE

被引：611

作者：

SMITH, AFM ^{[1
]}

GELFAND, AE ^{[1
]}

机构：

[1] UNIV CONNECTICUT,DEPT STAT,STORRS,CT 06269

来源：

AMERICAN STATISTICIAN | 1992年 / 46卷 / 02期

关键词：

BAYESIAN INFERENCE; EXPLORATORY DATA ANALYSIS; GRAPHICAL METHODS; INFLUENCE; POSTERIOR DISTRIBUTION; PREDICTION; PRIOR DISTRIBUTION; RANDOM VARIATE GENERATION; SAMPLING RESAMPLING TECHNIQUES; SENSITIVITY ANALYSIS; WEIGHTED BOOTSTRAP;

D O I：

10.2307/2684170

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Even to the initiated, statistical calculations based on Bayes's Theorem can be daunting because of the numerical integrations required in all but the simplest applications. Moreover, from a teaching perspective, introductions to Bayesian statistics-if they are given at all-are circumscribed by these apparent calculational difficulties. Here we offer a straightforward sampling-resampling perspective on Bayesian inference, which has both pedagogic appeal and suggests easily implemented calculation strategies.

引用

页码：84 / 88

页数：5

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