BUGS

Astronomers tend to think in Bayesian way, but their Bayesian implementation is very limited. OpenBUGS, WinBUGS, GeoBUGS (BUGS for geostatistics; for example, modeling spatial distribution), R2WinBUGS (R BUGS wrapper) or PyBUGS (Python BUGS wrapper) could boost their Bayesian eagerness. Oh, by the way, BUGS stands for Bayesian inference Using Gibbs Sampling.

Disclaimer: I never did serious Bayesian computations so that information I provide here tends to be very shallow. Both statisticians and astronomers oriented by Bayesian ideals are very welcome to add advanced pieces of information.

Bayesian statistics is very much preferred in astronomy, at least here at Harvard Smithsonian Center for Astrophysics. Yet, I do not understand why astronomy data analysis packages do not include libraries, modules, or toolboxes for MCMC (porting scripts from Numerical Recipes or IMSL, or using Python does not count here since these are also used by engineers and scientists of other disciplines: my view is also restricted thanks to my limited experience in using astronomical data analysis packages like ciao, XSPEC, IDL, IRAF, and AIPS) similar to WinBUGS or OpenBUGS. Most of Bayesian analysis in astronomy has to be done from the scratch, which drives off simple minded people like me (I prefer analytic forms and estimators than posterior chains). I hope easily implementable Bayesian Data Analysis modules come along soon to current astronomical data analysis systems for any astronomers who only had a lecture about Bayes theorem and Gibbs sampling. Perhaps, BUGS can be a role model to develop such modules.

As listed, one does not need R to use BUGS. WinBUGS is both stand alone and R implementable. PyBUGS can be handy since python is popular among astronomers. I heard that MATLAB (its open source counterpart, OCTAVE) has its own tools to maneuver Bayesian Data Analysis relatively easily. There are many small MCMC modules to solve particular problems in astronomy but none of them are reported to be robust enough so as to be applied in other type data sets. Not many have the freedom of choosing models and priors.

Hopefully, well knowledged Bayesians contribute in developing modules for Bayesian data analysis in astronomy. I don’t like to see contour plots, obtained from brute-forceful and blinded χ2 fitting, claimed to be bivariate probability density profiles. I’d like to project the module development like the way that BUGS is developed in astronomical data analysis packages with various Bayesian libraries. Here are some web links about BUGS:
The BUGS Project
WinBUGS
OpenBUGS
Calling WinBUGS 1.4 from other programs

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