Functions for computing and visualizing
generalized canonical discriminant analyses and canonical correlation analysis
for a multivariate linear model.
Traditional canonical discriminant analysis is restricted to a one-way 'MANOVA'
design and is equivalent to canonical correlation analysis between a set of quantitative
response variables and a set of dummy variables coded from the factor variable.
The 'candisc' package generalizes this to higher-way 'MANOVA' designs
for all factors in a multivariate linear model,
computing canonical scores and vectors for each term. The graphic functions provide low-rank (1D, 2D, 3D)
visualizations of terms in an 'mlm' via the 'plot.candisc' and 'heplot.candisc' methods. Related plots are
now provided for canonical correlation analysis when all predictors are quantitative.
| Version: |
0.8-3 |
| Depends: |
R (≥ 3.5.0), car, heplots (≥ 0.8-6), graphics, stats |
| Suggests: |
rgl, corrplot, knitr, rmarkdown, MASS, rpart, rpart.plot |
| Published: |
2020-04-22 |
| Author: |
Michael Friendly [aut, cre],
John Fox [aut] |
| Maintainer: |
Michael Friendly <friendly at yorku.ca> |
| BugReports: |
https://github.com/friendly/candisc/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
candisc results |