Package: mixedMem 1.2.0

Y. Samuel Wang

mixedMem: Tools for Discrete Multivariate Mixed Membership Models

Fits mixed membership models with discrete multivariate data (with or without repeated measures) following the general framework of Erosheva et al (2004). This package includes a Variational EM and MCMC estimation approaches. Currently supported data types are Bernoulli, multinomial and rank (Plackett-Luce). The extended GoM model with fixed stayers from Erosheva et al (2007) is now also supported. See Airoldi et al (2014) for other examples of mixed membership models.

Authors:Y. Samuel Wang [aut, cre], Elena A. Erosheva [aut]

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mixedMem.pdf |mixedMem.html✨
mixedMem/json (API)

# Install 'mixedMem' in R:
install.packages('mixedMem', repos = c('https://ysamwang.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ysamwang/mixedmem/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • ANES - Responses from 1983 American National Election Survey Pilot
  • ct_hagdu - Responses Chlamydia trachomatis test data

On CRAN:

Conda:

openblascpp

2.15 score 1 stars 14 scripts 151 downloads 17 exports 7 dependencies

Last updated 9 years agofrom:d830b4de68. Checks:12 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesFAILMar 29 2025
R-4.5-win-x86_64ERRORMar 29 2025
R-4.5-mac-x86_64ERRORMar 29 2025
R-4.5-mac-aarch64ERRORMar 29 2025
R-4.5-linux-x86_64ERRORMar 29 2025
R-4.4-win-x86_64ERRORMar 29 2025
R-4.4-mac-x86_64ERRORMar 29 2025
R-4.4-mac-aarch64ERRORMar 29 2025
R-4.4-linux-x86_64ERRORMar 29 2025
R-4.3-win-x86_64ERRORMar 29 2025
R-4.3-mac-x86_64ERRORMar 29 2025
R-4.3-mac-aarch64ERRORMar 29 2025

Exports:computeAICcomputeBICcomputeELBOentropyPlotfindLabelsgetPosteriorEstimateshellingerDistancesmixedMemModelMCMCmixedMemModelVarInfmmMCMCFitmmVarInfFitpermuteLabelsplotPosteriorrmixedMemtheta.tablevizMemvizTheta

Dependencies:BHgtoolsR.methodsS3R.ooR.utilsRcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Tools for fitting discrete multivariate mixed membership modelsmixedMem-package mixedMem
Responses from 1983 American National Election Survey PilotANES
Compute the approximate AICcomputeAIC
Compute the approximate BICcomputeBIC
Compute a lower bound on the log-likelihood (ELBO)computeELBO
Responses Chlamydia trachomatis test datact_hagdu
Mixed Membership VisualizationentropyPlot
Mixed Membership Post-Processing 'findLabels' finds the optimal permutation of labels that minimizes the weighted squared difference between the arrays of subpopulation parameters from a fitted mixed membership model, theta and a given comparison model.findLabels
Mixed Membership Post-Processing for MCMC method 'getPosteriorEstimates'getPosteriorEstimates
Mixed membership models post-processinghellingerDistances
Constructor for a Mixed Membership Model object which can be fit through MCMCmixedMemModelMCMC
Constructor for a Mixed Membership Model object which can be fit using variational inferencemixedMemModelVarInf
Fit Mixed Membership models using a Metropolis Hastings within Gibbs MCMC samplermmMCMCFit
Fit Mixed Membership models using variational EMmmVarInfFit
Mixed Membership Post-ProcessingpermuteLabels
Plot a Mixed Membership Modelplot.mixedMemModelMCMC
Plot a Mixed Membership Modelplot.mixedMemModelVarInf
Mixed Membership Post-Processing for MCMC method 'plotPosterior'plotPosterior
Simulate Data from a discrete mixed membership modelrmixedMem
Summary of a Mixed Membership Modelsummary.mixedMemModelMCMC
Summary of a Mixed Membership Modelsummary.mixedMemModelVarInf
Print the theta estimates for each sub-populationtheta.table
Mixed Membership VisualizationvizMem
Mixed Membership VisualizationvizTheta