本身不是做统计学的。兴趣倒是不小。刚开始关注Bayes。到目前，看到几本这方面的书。各有不同，但都有参考价值：

1. 适合非统计专业的人阅读的入门级

1.1 Introduction to WinBUGS for Ecologists
       向生态学者介绍 Bayesian Modeling的书。浅显易懂。可惜，支持这本书网站一直打不开，还没有运行过它的例子。如果你仅了解最基本的统计回归，你就可以通过这本书开始 Bayesian 了。

1.2 A First Course in Bayesian Statistical Methods
       这本和上本类似。公式相对多了点，但完全适合非专业人士自学。作者在前言里这样写道”My experience has been that once a student understands the basic idea of posterior sampling, their data analyses quickly become more creative and meaningful, using relevant posterior predictive distributions and interesting functions of parameters.“ 看来，Bayesian不但有用而且好像很容易。

2. 高级别的

2.1 "Bayesian Data Analysis," by Gelman, Carlin, Stern, and Rubin (1995, 2004)
2.2  "Data Analysis Using Regression and Multilevel/Hierarchical Models," by Gelman and Hill (2007)
这两本只是翻了翻，follow 书中例子不难，想弄明白的话，似乎是做梦。但从应用角度来说，也是不可不读的书。

3. 未知级别

3.1 Bayes and Empirical Bayes Methods for Data Analysis
3.2 Bayesian Analysis for Population Ecology_R
3.3 Bayesian Analysis of Gene Expression Data
3.4 Bayesian Biostatistics
3.5 Bayesian Computation With R-2ed
3.6 Bayesian Disease Mapping Hierarchical Modeling in Spatial Epidemiology
3.7 Bayesian Methods for Ecology
3.8 Bayesian Modeling Using WinBUGS
3.9 Bayesian Statistical Modelling_R
3.10 Bayesian_core_a_practical_approach_to_computational
3.11 Introduction to Bayesian Scientific Computing-
3.12 Introducing Monte Carlo Methods with R
3.13 Introduction to Probability Simulation and Gibbs Sampling with R


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