In the documentation of mixture model ( https://docs.pymc.io/api/distributions/mixture.html ) I saw the following snippet: What’s the difference between the sigma in pm.Normal and the sigma in pm.Normal.dist? npop = 5 nd = (3, 4) with pm.Model() as model: mu = pm.Normal('mu', mu=np.arange(npop)…

The pm.Normal defines the prior distribution of the component means. pm.Normal.dist is the component-specific distribution. So the exact mean of each component is unknown but has the prior distribution given by pm.Normal and the random variables of a given component i are known to be distributed as …

On mixtures of normals in the documentation

Questions

pymclearner September 26, 2019, 5:26pm 4

Thank you for the answers and insights. @Dominik @junpenglao

Topic		Replies	Views
Defining prior as mixture of two normal distribution	5	811	July 21, 2022
Correctly specifying a model with a multimodal distribution version agnostic modeling	10	1153	May 14, 2022
How to use a DensityDist in a Mixture? Questions	4	1552	June 13, 2018
Mixture Model Dirichlet Questions	7	3054	June 1, 2018
Mixture of normal and AR(p) process? Questions	2	533	November 6, 2018

On mixtures of normals in the documentation

Related topics