candisc: Visualizing Generalized Canonical Discriminant and Canonical
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.
||R (≥ 2.10), car, heplots (≥ 0.8.6), graphics, stats
||Michael Friendly [aut, cre], John Fox [aut]
||Michael Friendly <friendly at yorku.ca>
||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]