Hi,

I just started with pymc and I’ve been documenting myself for a weeks

Maybe it’s a very stupid question but I can’t find how can I get the probabilities of

`P(theta = '1'|y = '80')`

`P(y = '50'|theta = '3')`

`P(theta = '1', y = '80')`

and get the graphic `P(theta|y)`

.

(Note that my prior is `theta`

, my prior is discrete and my ‘y’ distribution is continuous, so for me it’s valid to find the range of 80.0 to 80.99 for example)

in this simple model:

import pymc3 as pm

num_people = 100

with pm.Model() as model:

`theta = pm.BetaBinomial('θ', alpha=1., beta=1.,n=num_people) y = pm.TruncatedNormal('y', mu=theta, sigma=15, lower=0.0, upper=101.0) trace = pm.sample(10000, cores=1)`

I’d appreciate any help,

John.