Package: mixedMem 1.1.2
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 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.
Authors:
mixedMem_1.1.2.tar.gz
mixedMem_1.1.2.tar.gz(r-4.5-noble)mixedMem_1.1.2.tar.gz(r-4.4-noble)
mixedMem_1.1.2.tgz(r-4.4-emscripten)mixedMem_1.1.2.tgz(r-4.3-emscripten)
mixedMem.pdf |mixedMem.html✨
mixedMem/json (API)
# Install 'mixedMem' in R: |
install.packages('mixedMem', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 years agofrom:106a3d6d30. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 02 2024 |
R-4.5-linux-x86_64 | OK | Dec 02 2024 |
Exports:computeBICcomputeELBOfindLabelsmixedMemModelmmVarFitpermuteLabelsrmixedMemvizMemvizTheta
Dependencies:BHgtoolsRcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Tools for fitting discrete multivariate mixed membership models | mixedMem-package mixedMem |
Responses from 1983 American National Election Survey Pilot | ANES |
Compute the approximate BIC | computeBIC |
Compute a lower bound on the log-likelihood (ELBO) | computeELBO |
Mixed Membership Post-Processing | findLabels |
Point estimates from Gross and Manrique-Vallier 2014 | gmv_theta |
Constructor for a Mixed Membership Model Object | mixedMemModel |
Fit Mixed Membership models using variational EM | mmVarFit |
Mixed Membership Post-Processing | permuteLabels |
Plot a Mixed Membership Model | plot.mixedMemModel |
Simulate Mixed Membership Data | rmixedMem |
Summary of a Mixed Membership Model | summary.mixedMemModel |
Mixed Membership Visualization | vizMem |
Mixed Membership Visualization | vizTheta |