Closed
Description
When size is not specified, the base distribution is not resized and can broadcast with lower
/ upper
, with repeated draws.
import aesara.tensor as at
import pymc as pm
rng = at.random.default_rng(123)
x = pm.Censored.dist(pm.Normal.dist(0), lower=[-1, -1, -1], upper=[1, 1, 1], rngs=(rng,))
x.eval() # array([-0.98912135, -0.98912135, -0.98912135])
We need to do something like in:
pymc/pymc/distributions/timeseries.py
Lines 185 to 187 in 4702bd4