I am playing around with this simple tabular problem, and I was surprised to find that the Bernoulli likelihood only worked as expected for a single outcome. If I want to condition on observing 5 events (all True for instance), then it doesn’t seem to work (i.e., the posterior for bowl1 is incorrect). The equivalent binomial model works just fine. Why is this the case?
with pm.Model() as m: # Prior bowl1 = pm.Bernoulli('bowl1', 1/2) # Conditional probabality / Likelihood p_vanilla = pm.math.switch(bowl1, 3/4, 1/2) # vanilla = pm.Binomial('vanilla', n=5, p=p_vanilla, observed=5) # vanilla = pm.Binomial('vanilla', n=1, p=p_vanilla, observed=[True, True, True, True, True]) vanilla = pm.Bernoulli('vanilla', p=p_vanilla, observed=[True, True, True, True, True]) trace_m = pm.sample(500)
Thanks in advance for your input