can_lm

This function uses <code>candisc</code> to transform the responses in a
multivariate linear model to scores on canonical variables for a given term and then uses
those scores as responses in a linear (lm) or multivariate linear model (mlm).
The function constructs a model formula of the form <code>Can ~ terms</code> where
Can is the canonical score(s) and terms are the terms in the original mlm,
then runs lm() with that formula.

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.

Michael Friendly

candisc

Visualizing Generalized Canonical Discriminant and Canonical
Correlation Analysis

John Fox

can_lm function

<dl><dt>mod</dt>
<dd>A <code>mlm</code> object</dd>
<dt>term</dt>
<dd>One term in that model</dd>
<dt>...</dt>
<dd>Arguments passed to <code>candisc</code></dd></dl>

Arguments

Author

Transform a Multivariate Linear model mlm to a Canonical Representation — can_lm

<dl>

<dt>mod</dt>
<dd>A <code>mlm</code> object</dd>


<dt>term</dt>
<dd>One term in that model</dd>


<dt>...</dt>
<dd>Arguments passed to <code>candisc</code></dd>

</dl>

can_lm: Transform a Multivariate Linear model mlm to a Canonical Representation

Description

Usage

Value

Arguments

Author

See Also

Examples