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