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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.
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Package details |
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| Author | Éric Lacourse [aut], Roxane de la Sablonnière [aut], Charles-Édouard Giguère [aut, cre], Sacha Morin [aut], Robin Legault [aut], Félix Laliberté [aut], Zsusza Bakk [ctb] |
| Maintainer | Charles-Édouard Giguère <ce.giguere@gmail.com> |
| License | GPL-2 |
| Version | 0.1.2 |
| URL | https://github.com/Labo-Lacourse/StepMixr |
| Package repository | View on CRAN |
| Installation |
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