Hi, I defined a custom likelihood function I want to use in some model via DensityDist. This likelihood is defined up to a constant which I think is fine with the way PyMC3 works. However, I have difficulties in understanding the results I get by evaluating the likelihood. Here is the corresponding…

They are not the same because d is depend on t: d = pm.DiscreteUniform('d', lower=1, upper=N-t), which changing t also change the logp of d. You can have custom logp that are “up to a constant”, but the RVs in PyMC3 retained all the constants (unlike in Stan, which you need to change your way of wr…

Likelihood evaluation and DensityDist

Questions

Rom1P February 21, 2018, 8:39am 3

Thank you for your answer !

Topic		Replies	Views
Problem with pymc3.DensityDist() #2846 Questions from_github	3	2284	February 8, 2018
Likelihood Specification and DensityDist Questions doc	3	1025	October 5, 2021
How to set up a custom likelihood function for two variables Questions	8	13306	March 9, 2018
Creating custom likelihoods with DensityDist - what am I doing wrong? Questions	1	865	November 5, 2017
Custom likelihood functions with DensityDist Sharing	1	829	December 9, 2020

Likelihood evaluation and DensityDist

Related topics