candisc: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

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.

AuthorMichael Friendly [aut, cre], John Fox [aut]
Date of publication2016-11-11 00:07:23
MaintainerMichael Friendly <>
LicenseGPL (>= 2)

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cancor Man page
cancor.default Man page
cancor.formula Man page
candisc Man page
candiscList Man page
candiscList.mlm Man page
candisc.mlm Man page
candisc-package Man page
can_lm Man page
coef.cancor Man page
coef.candisc Man page
dataIndex Man page
Grass Man page
heplot3d.cancor Man page
heplot3d.candisc Man page
heplot3d.candiscList Man page
heplot.cancor Man page
heplot.candisc Man page
heplot.candiscList Man page
HSB Man page
plot.cancor Man page
plot.candisc Man page
plot.candiscList Man page
print.cancor Man page
print.cancor.redundancy Man page
print.candisc Man page
print.candiscList Man page
redundancy Man page
scores Man page
scores.cancor Man page
summary.cancor Man page
summary.candisc Man page
summary.candiscList Man page
varOrder Man page Man page
varOrder.mlm Man page
vecscale Man page
vectors Man page
vectors3d Man page
Wilks Man page
Wilks.cancor Man page
Wilks.candisc Man page
Wine Man page
Wolves Man page

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