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mixedMem (version 1.1.2)

Tools for Discrete Multivariate Mixed Membership Models

Description

Fits mixed membership models with discrete multivariate data (with or without repeated measures) following the general framework of Erosheva et al (2004). This package uses a Variational EM approach by approximating the posterior distribution of latent memberships and selecting hyperparameters through a pseudo-MLE procedure. 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.

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Version

Install

install.packages('mixedMem')

Monthly Downloads

198

Version

1.1.2

License

GPL (>= 2)

Maintainer

Y. Samuel Wang

Last Published

December 1st, 2020

Functions in mixedMem (1.1.2)

ANES

Responses from 1983 American National Election Survey Pilot
vizMem

Mixed Membership Visualization
computeBIC

Compute the approximate BIC
vizTheta

Mixed Membership Visualization
mixedMemModel

Constructor for a Mixed Membership Model Object
mmVarFit

Fit Mixed Membership models using variational EM
findLabels

Mixed Membership Post-Processing
computeELBO

Compute a lower bound on the log-likelihood (ELBO)
permuteLabels

Mixed Membership Post-Processing
plot.mixedMemModel

Plot a Mixed Membership Model
mixedMem-package

Tools for fitting discrete multivariate mixed membership models
gmv_theta

Point estimates from Gross and Manrique-Vallier 2014
rmixedMem

Simulate Mixed Membership Data
summary.mixedMemModel

Summary of a Mixed Membership Model