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by dustintran
3924 days ago
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Hi, stan dev here. I think viewing Stan as a better BUGS is helpful but limiting. The syntax is similar, but the class of models Stan fits is far more general. The class of algorithms we have available also goes beyond MCMC, e.g., variational inference, optimization, and interfaces to Stan exist on all primary programming languages. It's more helpful to think of Stan as its own probabilistic programming language, and arguably the biggest entity with the largest user base. |
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This is mostly true, but last time I checked, Stan still couldn't sample discrete variables like BUGS can. Stan can only fit models with discrete parameters (e.g. finite mixtures) if the programmer is smart enough to integrate them out.