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.

Version: 1.0
Depends: directlabels, proto, ggplot2
Imports: Rcpp (≥ 0.11.4), MASS, VGAM, truncnorm
LinkingTo: Rcpp, RcppArmadillo
Published: 2015-07-23
Author: Marc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito
Maintainer: Marc Ratkovic <ratkovic at princeton.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: Psychometrics
CRAN checks: SparseFactorAnalysis results

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Reference manual: SparseFactorAnalysis.pdf
Package source: SparseFactorAnalysis_1.0.tar.gz
Windows binaries: r-devel: SparseFactorAnalysis_1.0.zip, r-release: SparseFactorAnalysis_1.0.zip, r-oldrel: SparseFactorAnalysis_1.0.zip
OS X Mavericks binaries: r-release: SparseFactorAnalysis_1.0.tgz, r-oldrel: SparseFactorAnalysis_1.0.tgz

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