SparseFactorAnalysis: Scaling Count and Binary Data with Sparse Factor Analysis

Multidimensional scaling provides a means of uncovering a latent structure underlying observed data, while estimating the number of latent dimensions. This package presents a means for scaling binary and count data, for example the votes and word counts for legislators. Future work will include an EM implementation and extend this work to ordinal and continuous data.

Install the latest version of this package by entering the following in R:
install.packages("SparseFactorAnalysis")
AuthorMarc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito
Date of publication2015-07-23 07:05:04
MaintainerMarc Ratkovic <ratkovic@princeton.edu>
LicenseGPL (>= 2)
Version1.0

View on CRAN

Files

src
src/Makevars
src/grad_est.h
src/grad_est.cpp
src/hmc4sfa.cpp
src/test_gamma_pois.cpp
src/Makevars.win
src/RcppExports.cpp
src/test_gamma_pois.h
NAMESPACE
R
R/Functions_Count.R R/RcppExports.R R/FunctionsInternal_Count.R R/sfa_utility.R R/FunctionsInternal_Count_EM.R
MD5
DESCRIPTION
man
man/sfa-internal.Rd man/sfa-package.Rd man/plot.sfa.Rd man/summary.sfa.Rd man/sfa.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.