Hi I’m going to write a distribution which is not in the pymc3’s library. How should I do that? and how should I incorporate that in the codes?? (For example, suppose that Cauchy distribution is not available and I want to write that)

There is a very crude guide in here: Probability Distributions in PyMC3 — PyMC3 3.10.0 documentation You have two options, to create a standard distribution by inheriting from the right subclasses (Discrete, Continuous, PositiveContinuous, etc), or using a pm.Densitydist that takes a callable logp …

Writing a new distribution

Questions

jonsedar March 24, 2021, 5:55am 10

Generalized EV might be useful - I’ve written an InverseWeibull for a recent project that I intend to PR once I get a minute!

2 Likes

Topic		Replies	Views
Porting PyMC code to run on PyMC3 how to create a stochastic subclass distribution? Questions development	2	882	January 8, 2020
Drawing values from custom distribution Questions	8	1041	September 14, 2022
Recommended way to create a new discrete distribution? Questions development	3	1819	February 4, 2020
Problem with pymc3.DensityDist() #2846 Questions from_github	3	2284	February 8, 2018
Posterior Predictive Check for Density Dist Questions	4	397	November 17, 2021

Writing a new distribution

Related topics