README.md

In clintpgeorge/clda: Approximate Inference Algorithms for the Compound Latent Dirichlet Allocation Model

Algorithms for the Compound Latent Dirichlet Allocation Model

This R package, clda, implements the following Markov chain Monte Carlo (MCMC) and variational methods for the compound latent Dirichlet allocation (cLDA) model. Auxiliary variable update within Gibbs sampler (AGS) Metropolis adjusted Langevin algorithm within Gibbs sampler (MGS) * Variational Expectation Maximization (VEM)

For package documentation run

help("clda")

in an R console. All major functions and datasets are documented and linked to the package index.

To see all demo R scripts available in this package, run

demo(package="clda")

in an R console. These demo scripts require commandline arguments for execution. Please see the documentation provided in each script before execution.

Authors

• Clint P. George (Please contact for questions and comments)
• Wei Xia
• George Michailidis

Dependencies

This package uses the following R packages, which are already included in this R package. Rcpp RcppArmadillo based on the Armadillo C++ package * lattice

Installation Guide

• Download the package source from Git Download Link
• Unzip the dowloaded file and rename the folder clda-master to clda
• To install clda run R CMD INSTALL clda on the commandline
• To uninstall clda run R CMD REMOVE clda on the commandline

clintpgeorge/clda documentation built on May 13, 2019, 8 p.m.