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candisc  

Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis
View on CRAN: Click here


Download and install candisc package within the R console
Install from CRAN:
install.packages("candisc")

Install from Github:
library("remotes")
install_github("cran/candisc")

Install by package version:
library("remotes")
install_version("candisc", "0.9.0")



Attach the package and use:
library("candisc")
Maintained by
Michael Friendly
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2008-04-14
Latest Update: 2021-10-07
Description:
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.
How to cite:
Michael Friendly (2008). candisc: Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis. R package version 0.9.0, https://cran.r-project.org/web/packages/candisc. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.5-9 (2008-04-14 20:16), 0.5-10 (2008-11-10 11:45), 0.5-13 (2009-02-03 21:03), 0.5-15 (2009-06-14 21:07), 0.5-16 (2009-11-19 14:00), 0.5-18 (2010-07-29 17:47), 0.5-19 (2010-09-19 20:30), 0.5-21 (2011-12-11 11:41), 0.6-0 (2013-01-23 07:26), 0.6-1 (2013-01-30 15:17), 0.6-2 (2013-02-12 18:11), 0.6-3 (2013-03-15 07:23), 0.6-5 (2013-06-12 08:15), 0.6-7 (2015-04-19 07:30), 0.7-0 (2016-04-27 13:30), 0.7-2 (2016-11-11 00:07), 0.8-0 (2017-09-19 19:18), 0.8-3 (2020-04-22 14:02), 0.8-5 (2021-01-22 17:30), 0.8-6 (2021-10-07 19:10)
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