Labo-Lacourse / stepmix

A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
https://stepmix.readthedocs.io/en/latest/index.html
MIT License
54 stars 4 forks source link

Wrong number of parameters in mixed models #41

Closed sachaMorin closed 1 year ago

sachaMorin commented 1 year ago

The loop in nested.py only reassigns the parameter count instead of summing it properly.