candisc0.9.0 package

Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis

dataIndex

Indices of observations in a model data frame

can_lm

Transform a Multivariate Linear model mlm to a Canonical Representatio...

cancor

Canonical Correlation Analysis

candisc-package

Visualizing Generalized Canonical Discriminant and Canonical Correlati...

candisc

Canonical discriminant analysis

candiscList

Canonical discriminant analyses

heplot.cancor

Canonical Correlation HE plots

heplot.candisc

Canonical Discriminant HE plots

heplot.candiscList

Canonical Discriminant HE plots

plot.cancor

Canonical Correlation Plots

predictor.names

Get predictor names from a lm-like model

redundancy

Canonical Redundancy Analysis

varOrder

Order variables according to canonical structure or other criteria

vecscale

Scale vectors to fill the current plot

vectors

Draw Labeled Vectors in 2D or 3D

Wilks

Wilks Lambda Tests for Canonical Correlations

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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.

  • Maintainer: Michael Friendly
  • License: GPL (>= 2)
  • Last published: 2024-05-06

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