predictor.names

predictor.names.default

Get predictor names from a <code>lm</code>-like model

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

predictor.names function

<dl><dt>model</dt>
<dd>Model object</dd>
<dt>...</dt>
<dd>other arguments (ignored)</dd></dl>

Arguments

<ul>
<li><code>predictor.names(default)</code>: <code>"default"</code> method.</li>
</ul>

Methods (by class)

Get predictor names from a lm-like model — predictor.names

<dl>

<dt>model</dt>
<dd>Model object</dd>


<dt>...</dt>
<dd>other arguments (ignored)</dd>

</dl>

predictor.names: Get predictor names from a `lm`-like model

Description

Usage

Value

Arguments

Methods (by class)

Examples