Interface to 'Python' Package 'StepMix'
Description
This is an interface for the 'Python' package
'StepMix'. It is 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 based on pseudolikelihood
theory. Additional features include support for covariates and distal outcomes,
various simulation utilities, and non-parametric bootstrapping, which allows
inference in semi-supervised and unsupervised settings.