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stepmixr

Interface to 'Python' Package 'StepMix'

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. Software paper available at <doi:10.18637/jss.v113.i08>.

Versions across snapshots

VersionRepositoryFileSize
0.1.3 rolling linux/jammy R-4.5 stepmixr_0.1.3.tar.gz 63.2 KiB
0.1.3 rolling linux/noble R-4.5 stepmixr_0.1.3.tar.gz 63.2 KiB
0.1.3 rolling source/ R- stepmixr_0.1.3.tar.gz 11.3 KiB
0.1.3 latest linux/jammy R-4.5 stepmixr_0.1.3.tar.gz 63.2 KiB
0.1.3 latest linux/noble R-4.5 stepmixr_0.1.3.tar.gz 63.2 KiB
0.1.3 latest source/ R- stepmixr_0.1.3.tar.gz 11.3 KiB
0.1.3 2026-04-26 source/ R- stepmixr_0.1.3.tar.gz 11.3 KiB
0.1.3 2026-04-23 source/ R- stepmixr_0.1.3.tar.gz 11.3 KiB
0.1.3 2026-04-09 windows/windows R-4.5 stepmixr_0.1.3.zip 65.9 KiB
0.1.2 2025-04-20 source/ R- stepmixr_0.1.2.tar.gz 10.7 KiB

Dependencies (latest)

Imports