Simple Principal Components Analysis (PCA) and (Multiple)
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: |
0.5.0 |
| Depends: |
R (≥ 3.5) |
| Imports: |
arkhe (≥ 1.4.0), graphics, grDevices, methods |
| Suggests: |
ggplot2, khroma, knitr, rmarkdown, rsvg, svglite, tinysnapshot, tinytest |
| Published: |
2023-11-24 |
| Author: |
Nicolas Frerebeau 
[aut, cre] (Université Bordeaux Montaigne),
Jean-Baptiste Fourvel
[ctb] (CNRS),
Brice Lebrun
[ctb] (Université Bordeaux Montaigne),
Université Bordeaux Montaigne [fnd],
CNRS [fnd] |
| 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 |