I am having trouble implementing Normal distribution with mu that is a shared variable. See below example code: product_mu_shared = shared(0.0) product_sd = 0.1 total_quantity_shared = shared(np.array([0.0, 0.1, 0.2])) with pm.Model() as quantity_model: # Priors a = pm.Lognormal('…

As a workaround for now, you can assign a test value to Normal: d = pm.Normal('d', mu=product_mu_shared, sd=product_sd, testval=0.) FYI, you cannot put observed in a Deterministic node.

[image] benyi-mikara: --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-6131815c61f7> in <module>() 4 a = pm.Lognormal(‘a’,mu=product_mu_shared, sd=product_sd) 5 b = pm.Normal(‘b’,mu=0.0, sd=product_sd) ----> …

Normal distribution throws errors when using shared variables

Questions

junpenglao August 7, 2018, 4:36am 2

This is a bug, could you please raise an issue on github?

Changing prior during inference

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Normal distribution throws errors when using shared variables

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