dimensio: Multivariate Data Analysis
Simple Principal Components Analysis (PCA) and Correspondence
Analysis (CA) based on the Singular Value Decomposition (SVD). This
package provides S4 classes and methods to compute, extract, summarize
and visualize results of multivariate data analysis. It also includes
methods for partial bootstrap validation described in Greenacre (1984)
<isbn:978-0-12-299050-2> and Lebart et al. (2006)
<isbn:978-2-10-049616-7>.
Version: |
0.4.0 |
Depends: |
R (≥ 3.5) |
Imports: |
ggplot2, graphics, grDevices, methods, rlang |
Suggests: |
khroma, knitr, rmarkdown, rsvg, svglite, tinysnapshot, tinytest |
Published: |
2023-08-23 |
Author: |
Nicolas Frerebeau
[aut, cre] (Université Bordeaux Montaigne),
Jean-Baptiste Fourvel
[ctb] (CNRS),
Brice Lebrun
[ctb] (Université Bordeaux Montaigne) |
Maintainer: |
Nicolas Frerebeau <nicolas.frerebeau at u-bordeaux-montaigne.fr> |
BugReports: |
https://github.com/tesselle/dimensio/issues |
License: |
GPL (≥ 3) |
URL: |
https://packages.tesselle.org/dimensio/,
https://github.com/tesselle/dimensio |
NeedsCompilation: |
no |
Citation: |
dimensio citation info |
Materials: |
README NEWS |
CRAN checks: |
dimensio results |
Documentation:
Downloads:
Reverse dependencies:
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