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SparseFactorAnalysis  

Scaling Count and Binary Data with Sparse Factor Analysis
View on CRAN: Click here


Download and install SparseFactorAnalysis package within the R console
Install from CRAN:
install.packages("SparseFactorAnalysis")

Install from Github:
library("remotes")
install_github("cran/SparseFactorAnalysis")

Install by package version:
library("remotes")
install_version("SparseFactorAnalysis", "1.0")



Attach the package and use:
library("SparseFactorAnalysis")
Maintained by
Marc Ratkovic
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-07-23
Latest Update:
Description:
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.
How to cite:
Marc Ratkovic (2015). SparseFactorAnalysis: Scaling Count and Binary Data with Sparse Factor Analysis. R package version 1.0, https://cran.r-project.org/web/packages/SparseFactorAnalysis. Accessed 04 Jun. 2026.
Previous versions and publish date:
1.0 (2015-07-23 07:05)
Other packages that cited SparseFactorAnalysis R package
View SparseFactorAnalysis citation profile
Other R packages that SparseFactorAnalysis depends, imports, suggests or enhances
Functions, R codes and Examples using the SparseFactorAnalysis R package
Some associated functions: plot.sfa . sfa-internal . sfa-package . sfa . summary.sfa . 
Some associated R codes: FunctionsInternal_Count.R . FunctionsInternal_Count_EM.R . Functions_Count.R . RcppExports.R . sfa_utility.R .  Full SparseFactorAnalysis package functions and examples
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