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copied!<p>Stan and rstan should run on Linux, Mac, or Windows that supports the dependencies. We have not tested on BSD or Oracle, but we expect them to work with either the g++ or clang compilers (although not the Oracle compilers).</p> <p>There is no explicitly parallel code in Stan or rstan but neither is there any code that prevents the binary from being executed by several processes simultaneously. For example, if you use Stan from the command line in a bash shell, you could do something like</p> <pre><code>./my_model --data=my_data.dump --seed=12345 --chain_id=1 --samples=samples_1.csv & ./my_model --data=my_data.dump --seed=12345 --chain_id=2 --samples=samples_2.csv & </code></pre> <p>and so forth for as many chains as you like. It is important to use the same seed but different chain_id when executing in parallel.</p> <p>If you are using the rstan package, you can call the main <code>stan()</code> function using any of the parallel engines supported by R and your operating system. Again, it is best to pass the same seed and different chain_id. As of <code>rstan v1.0.3</code> (not released yet), there is a function called <code>sflist2stanfit()</code> that takes a list of <code>stanfit</code> objects that may have been generated in parallel and combines them into a single <code>stanfit</code> object for analysis.</p> <p>For more information, there is a thread devoted to parallel execution at</p> <p><a href="https://groups.google.com/d/topic/stan-users/3goteHAsJGs/discussion">https://groups.google.com/d/topic/stan-users/3goteHAsJGs/discussion</a></p>

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