Mixture of hierarchical model

[junpenglao]

Also, you might find some inspiration from this question:

Gaussian Mixture of regression

df.csv (94.7 KB) Hello, I’m just curious to know why I’m getting two different results in the Mixture of regression. I tried to standardize the data but still obtained different results from the two model setups. Below are codes used in the analysis. I have also attached the data. Model 1: k = 2 with pm.Model() as Mixture_regression1: # Priors for weight parameter π1 = pm.Uniform('π1', 0, 1) π2 = pm.Deterministic('π2', 1. - π1) # Priors for unknown model parameters …

I had two notebook that explore different parameterization and inference:
https://github.com/junpenglao/Planet_Sakaar_Data_Science/blob/master/PyMC3QnA/mixture/Mixture_discourse.ipynb
https://github.com/junpenglao/Planet_Sakaar_Data_Science/blob/master/PyMC3QnA/mixture/Mixture_discourse_order.ipynb