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stepmixr
View on CRAN: Click
here
Download and install stepmixr package within the R console
Install from CRAN:
install.packages("stepmixr")
Install from Github:
library("remotes")
install_github("cran/stepmixr")
Install by package version:
library("remotes")
install_version("stepmixr", "0.1.2")
Attach the package and use:
library("stepmixr")
Maintained by
Charles-Édouard Giguère
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.stepmixr . stepmixr results . stepmixr.pdf . stepmixr_0.1.2.tar.gz . stepmixr_0.1.2.zip . stepmixr_0.1.2.zip . stepmixr_0.1.2.zip . stepmixr_0.1.2.tgz . stepmixr_0.1.2.tgz . stepmixr_0.1.2.tgz . stepmixr_0.1.2.tgz . stepmixr archive . https://CRAN.R-project.org/package=stepmixr .
First Published: 2022-11-18
Latest Update: 2024-01-09
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.
How to cite:
Charles-Édouard Giguère (2022). stepmixr: Interface to 'Python' Package 'StepMix'. R package version 0.1.2, https://cran.r-project.org/web/packages/stepmixr. Accessed 20 Apr. 2025.
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View stepmixr citation profile
Other R packages that stepmixr depends,
imports, suggests or enhances
Complete documentation for stepmixr
Functions, R codes and Examples using
the stepmixr R package
Some associated functions: Datasets . bootstrap . bootstrap_stats . fit . install.stepmix . mixed_descriptor . predict . savefit . stepmix .
Some associated R codes: Datasets.R . stepmix.R . Full stepmixr package functions and examples
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