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I have a an MCMC sample file containing a list of points in parameter space. I have the value of the parameters in my model at each point, and the likelihood at each point.

Of course I also have the prior ranges for each parameter.

How can I calculate the model evidence? I mean it's just an integral of the likelihoods over all the parameters with. Can PYMC do it?

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    $\begingroup$ See @Xi'an's excellent answer to my question here. $\endgroup$ – lacerbi Feb 15 '17 at 13:05
  • $\begingroup$ Thanks. Nested sampling seems to be the quickest and easiest method. If I order my points according to likelihood, I obtain more or less a nested sampling output. Or do I? $\endgroup$ – Itinerant Feb 16 '17 at 0:30

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