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stepmixr (version 0.1.2)

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.

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Install

install.packages('stepmixr')

Monthly Downloads

210

Version

0.1.2

License

GPL-2

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Maintainer

Charlesdouard Gigure

Last Published

January 9th, 2024

Functions in stepmixr (0.1.2)

Datasets

Series of function to simulate data.
bootstrap_stats

Non-parametric boostrap of StepMix estimator.
predict.stepmix.stepmix.StepMix

Predict the membership (probabilities) using the fit of the stepmix python package.
fit

Fit a mixture using the stepmix python package.
mixed_descriptor

Utility function for mixture using mixed description.
install.stepmix

Install stepmix python package into python via reticulate.
bootstrap

Non-parametric bootstrap of StepMix estimator.
savefit

Save the fit of a mixture using the stepmix python package.
stepmix

R interface to stepmix in StepMix python.