Package: stepmixr 0.1.2

Charles-Édouard Giguère

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.

Authors: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]

stepmixr_0.1.2.tar.gz
stepmixr_0.1.2.zip(r-4.5)stepmixr_0.1.2.zip(r-4.4)stepmixr_0.1.2.zip(r-4.3)
stepmixr_0.1.2.tgz(r-4.4-any)stepmixr_0.1.2.tgz(r-4.3-any)
stepmixr_0.1.2.tar.gz(r-4.5-noble)stepmixr_0.1.2.tar.gz(r-4.4-noble)
stepmixr_0.1.2.tgz(r-4.4-emscripten)stepmixr_0.1.2.tgz(r-4.3-emscripten)
stepmixr.pdf |stepmixr.html✨
stepmixr/json (API)

Peer review:

Bug tracker:https://github.com/labo-lacourse/stepmixr/issues

On CRAN:

18 exports 1 stars 1.26 score 12 dependencies 5 scripts 261 downloads

Last updated 4 months agofrom:ca9cc62cb1. Checks:OK: 7. Indexed: yes.

Exports:bakk_measurementsbootstrapbootstrap_statscheck_pystepmix_versiondata_bakk_completedata_bakk_covariatedata_bakk_responsedata_gaussian_diagdata_generation_gaussianfitidentify_coefinstall.stepmixloadfitmixed_descriptorpredict_probarandom_nansavefitstepmix

Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithr