cc: Canonical Correlation Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

The function performs Canonical Correlation Analysis to highlight correlations between two data matrices. It complete the cancor() function with supplemental numerical and graphical outputs and can handle missing values.

Usage

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cc(X, Y)

Arguments

X

numeric matrix (n * p), containing the X coordinates.

Y

numeric matrix (n * q), containing the Y coordinates.

Details

The canonical correlation analysis seeks linear combinations of the 'X' variables which are the most correlated with linear combinations of the 'Y' variables.

Let PX and PY be the projector onto the respective column-space of X and Y. The eigenanalysis of PXPY provide the canonical correlations (square roots of the eigenvalues) and the coefficients of linear combinations that define the canonical variates (eigen vectors).

Value

A list containing the following components:

cor

canonical correlations

names

a list containing the names to be used for individuals and variables for graphical outputs

xcoef

estimated coefficients for the 'X' variables as returned by cancor()

ycoef

estimated coefficients for the 'Y' variables as returned by cancor()

scores

a list returned by the internal function comput() containing individuals and variables coordinates on the canonical variates basis.

Author(s)

Sébastien Déjean, Ignacio González

References

www.lsp.ups-tlse.fr/CCA

See Also

rcc, plt.cc

Examples

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data(nutrimouse)
X=as.matrix(nutrimouse$gene[,1:10])
Y=as.matrix(nutrimouse$lipid)
res.cc=cc(X,Y)
plot(res.cc$cor,type="b")
plt.cc(res.cc)

Example output

Loading required package: fda
Loading required package: splines
Loading required package: Matrix

Attaching package: 'fda'

The following object is masked from 'package:graphics':

    matplot

Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.1-1 (2017-07-02) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction 
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

Attaching package: 'spam'

The following objects are masked from 'package:base':

    backsolve, forwardsolve

Loading required package: maps

CCA documentation built on March 1, 2021, 9:06 a.m.