(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
Steve Cohen writes:
As someone who has been working with Bayesian statistical models for the past several years, I [Cohen] have been challenged recently to describe the difference between Bayesian Networks (as implemented in BayesiaLab software) and modeling and inference using MCMC methods.
I hope you have the time to give me (or to write on your blog) and relatively simple explanation that an advanced layman could understand.
My reply:
I skimmed the above website but I couldn’t quite see what they do. My guess is that they use MCMC and also various parametric approximations such as variational Bayes. They also seem to have something set up for decision analysis.
My guess is that, compared to a general-purpose tool such as Stan, this Bayesia software is more accessible to non-academics in particular application areas (in this case, it looks like business marketing). But I can’t be sure.
I’ve also heard about another company that looks to be doing something similar: https://www.priorknowledge.com/
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