Hi All, I need help to understand what methods I can use to evaluate my fitted model if I don’t know how to sample from the custom distribution I implemented. In a bit more detail, A lot of times, I have to implement a custom likelihood function because the distribution is not implemented in PyMC,…

To answer your original general question, my scattered replies still apply. Many times PyMC has the distribution or the building blocks needed to create the distribution. This may require using meta distributions like pm.Censored or pm.Mixture and sometimes these need building blocks that are not p…

Perform model fit evaluation in Bayesian way when sampling from the custom distribution is not known

Questions v5

ricardoV94 October 20, 2023, 3:55pm 10

If there’s a Wald then your life is much easier. Just jump to the step where I created the shifted wald and use pm.Wald directly.

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Perform model fit evaluation in Bayesian way when sampling from the custom distribution is not known

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