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 multi-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.

person(given = "John", family = "Fox", role="aut"))
Author: Michael Friendly [aut, cre], John Fox [aut]
Description: Functions for computing and visualizing
generalized canonical discriminant analyses and canonical correlation analysis
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.

Package: candisc
Type: Package
Title: Visualizing Generalized Canonical Discriminant and Canonical
Correlation Analysis
Version: 0.8-0
Date: 2017-09-15
Depends: car, heplots (>= 0.8-6), graphics, stats
Suggests: rgl, corrplot, knitr, rmarkdown, MASS, rpart, rpart.plot
LazyLoad: yes
LazyData: yes
Authors@R: c(person(given = "Michael", family = "Friendly", role=c("aut", "cre"), email="friendly@yorku.ca"),
person(given = "John", family = "Fox", role="aut"))
Author: Michael Friendly [aut, cre], John Fox [aut]
Maintainer: Michael Friendly <friendly@yorku.ca>
Description: 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.
License: GPL (>= 2)
Packaged: 2017-09-19 15:48:42 UTC; Friendly
VignetteBuilder: knitr
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-09-19 17:18:42 UTC