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I was wondering if there is some mechanism in pymc3 to re-run a model with new data. After setting up the model and before sampling, I assume that pymc3 does some optimization (and compilation?) of the model which takes quite some time. I would like to setup the model once, and then run a long sequence different (independent) data sets through it.

I tried setting up the model outside a loop (defining all the priors, etc.) and only updating the likelihood with new measurements inside the loop (and run the sampling inside). The estimates, however, do not change with changing data. Hence I think the model is always using the data provided first.

Many thanks and best regards

Jan

Jan Tünnermann
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    Check [this issue](https://github.com/pymc-devs/pymc3/issues/511) at the PyMC3 repository and also [this](https://gist.github.com/twiecki/972496588bf69fbfbd98ed6b01a3c8a8) – aloctavodia Jul 28 '16 at 06:32

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