sfa-package: Sparse factor analysis for mixed binary and count data.
In SparseFactorAnalysis: Scaling Count and Binary Data with Sparse Factor Analysis
Description
Details
Author(s)
References
Description
Multi-dimensional scaling provides a means of uncovering a latent structure underlying observed data. This package presents a means for scaling binary and count data, for example the votes and word counts for legislators.
Details
Package: SparseFactorAnalysis
Type: Package
Version: 1.0
Date: 2015-03-21
License: GPL (>= 2)
Author(s)
Marc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito
Maintainer: Marc Ratkovic (ratkovic@princeton.edu)
References
In Song Kim, John Londregan, and Marc Ratkovic. 2015. "Voting, Speechmaking, and the Dimensions of Conflict in the US Senate." Working paper.
SparseFactorAnalysis documentation built on May 2, 2019, 6 a.m.
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Description Details Author(s) References
Description
Multi-dimensional scaling provides a means of uncovering a latent structure underlying observed data. This package presents a means for scaling binary and count data, for example the votes and word counts for legislators.
Details
| Package: | SparseFactorAnalysis |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2015-03-21 |
| License: | GPL (>= 2) |
Author(s)
Marc Ratkovic, In Song Kim, John Londregan, and Yuki Shiraito Maintainer: Marc Ratkovic (ratkovic@princeton.edu)
References
In Song Kim, John Londregan, and Marc Ratkovic. 2015. "Voting, Speechmaking, and the Dimensions of Conflict in the US Senate." Working paper.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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