svdvis-package: Singular Value Decomposition Visualization
In ncchung/svdvis: Singular Value Decomposition Visualization
Description
Visualize singular value decompositions (SVD), principal component analysis (PCA), factor analysis (FA) and related methods.
Details
Package: svdvis
Type: Package
Version: 1
License: GPL-2
Depends: ggplot2, GGally, gridExtra, scales, reshape2, RColorBrewer, grDevices
Providing convenient visualization functions for paired scatterplots, heat maps, parallel coordinates, and radial coordinates.
The package is developed for the outputs from singular value decompositions (SVD), principal component analysis (PCA), factor analysis (FA), and related methods.
Particularly, it focuses on exploring and visualizing multidimensional vectors (singular vectors, principal components, or factors) from dimension reduction techniques or latent variable models.
Author(s)
Neo Christopher Chung nchchung@gmail.com
ncchung/svdvis documentation built on May 23, 2019, 1:05 p.m.
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Description
Visualize singular value decompositions (SVD), principal component analysis (PCA), factor analysis (FA) and related methods.
Details
| Package: | svdvis |
| Type: | Package |
| Version: | 1 |
| License: | GPL-2 |
| Depends: | ggplot2, GGally, gridExtra, scales, reshape2, RColorBrewer, grDevices |
Providing convenient visualization functions for paired scatterplots, heat maps, parallel coordinates, and radial coordinates. The package is developed for the outputs from singular value decompositions (SVD), principal component analysis (PCA), factor analysis (FA), and related methods. Particularly, it focuses on exploring and visualizing multidimensional vectors (singular vectors, principal components, or factors) from dimension reduction techniques or latent variable models.
Author(s)
Neo Christopher Chung nchchung@gmail.com
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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