Bayesian programming (BUGS) references for different models

Yes, you can Google the key words to find the BUGS ( including WinBUGS and OpenBUGS) codes for your model but usually they will not work or you just can not understand what they are writing. You should firstly understand basic codes skill about BUGS:

1. Process for Building Bayesian Model
You could refer to the following picture.

Process for Building Bayesian Model 

see the example in the book,Applied Bayesian Statistics, pp.147

2. BUGS code structure
  "Data analysis using regression and multilevel/hierarchical models" (section 16.8, p.366)  gives excellent explanations about the BUGS code structure.  

3. How to perform the codes
"Bayesian Modeling Using WinBUGS" (chapter 3 and 4) gives clear pictures to teach you how to run your codes. 

4. Run BUGS through R
"Simple linear regression using R2OpenBUGS"
It is not easy to import your data in BUGS if your dataset is too big. Try to use R as a tool to manage data and deal with the MCMC results. This author offers a simple example (linear model) to teach you how to use these. If you want to totally include your BUGS code in R console, you should use sink and cat function , see this blog for a very vivid example. Other useful tricks for running BUGS within R could also found in book, Introduction to WinBUGS for Ecologists, (Appendix 1 - A List of WinBUGS Tricks).

5. Other special BUGS functions
Useful functions could be found here. More examples about using these should refer to The BUGS Book.


6. Bayes' Theory
I have gave a reading list for understanding this part in my another post. You should at least fully understand the first chapter of Bayesian Analysis for the Social Sciences.

Now you understand the basics, and you could try to search the codes about your interested models. The best and workable sources come from the books and journal articles.  Most authors below are very generous to provide the codes in their website. I will not provide these codes here but will suggest the references for you.

1. Efficiency estimation
(1)Stochastic frontier model
"Bayesian stochastic frontier analysis using WinBUGS"
The author (Professor Jim Griffin) provides the WinBUGS code in his website.
I depict their data structure as follows and you should also read their paper on page 165.

2. Panel data analysis
"Introduction to applied Bayesian statistics and estimation for social scientists" (ch.9)
Relevant theory of Bayesian panel data model could refer to Bayesian Econometrics (ch.7), Panel Data Modeling and Inference: A Bayesian Primer, Introduction to Modern Bayesian Econometrics (ch.7)
For specific panel data analysis demonstration:

• random coefficient model or varying-coefficients model: Bayesian Econometric Methods (ch. 12)

3. Multilevel/hierarchical models
"Data analysis using regression and multilevel/hierarchical models" especially chapter 17, p.305
"Applied Bayesian Hierarchical Methods"
"Scope economies in Australian distance education"

4. Econometrics
"An introduction to modern Bayesian Econometrics"

5. Rasch (IRT) Model
"Bayesian Estimation for the Rasch Model using WinBUGS"

6. Random Coefficient Dynamic Factor Models
"Bayesian Estimation of Random Coefficient Dynamic Factor Models"

7. Categorical models
Bayesian Models for Categorical Data, codes

8. Latent Growth Model
latent basis growth curve model with varying residual variances
latent basis growth curve model

9. Prediction
Linear regression: Bayesian Ideas and Data Analysis p. 241
Other models
"The BUGS Book"
"Bayesian modeling using WinBUGS"





This article will continuously be updated and I welcome anyone of you to post your experience here.