Hi there :) As the title says, I’m looking for a way to build a model where the variables are in same ranges with different values, however the result sampling suggest the sampling points are away from the switch constraints. So, what do you think about this? with pm.Model() as model: …

You can try to parametrize your model in a way that it respects the constraints naturally. For instance, instead of modelling rp and re directly, you can model the shift from the previous variable. with pm.Model(): rs = pm.Normal('rs', 800, 50) rp_shift = pm.LogNormal('rp_shift', 0, 1) re_shi…

Switch function has little constraint in sampling

Questions v3

ricardoV94 March 24, 2023, 5:59am 5

Potentials don’t play a role in prior or posterior predictive sampling since they are only part of the logp graph, not the random one.

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Switch function has little constraint in sampling

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