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yhat (version 2.0-2)

canonVariate: Canonical Commonality Analysis

Description

The canonCommonality function produces commonality data for a given canonical variable set. Using the variables in a given canonical set to partition the variance of the canonical variates produced from the other canonical set, commonality data is supplied for the number of canonical functions requested.

Usage

canonVariate(A, B, nofns)

Arguments

A

Matrix containing variable set A

B

Matrix containing variable set B

nofns

Number of canonical functions to analyze

Value

The function canonVariate returns commonality data for the canonical variable set input. For the number of functions requested, two tables are returned. The first table lists the commonality coefficients for each canonical function together with its contribution to the total effect, while the second table lists the unique and common effects for each regressor.

Details

For each canonical function, canonVariate: (a) creates a dataset that combines the matrix of variables for a given canonical set and the canonicate variate for the other canonical set; (b) calls commonalityCoefficients, passing the dataset, the name of the canonical variate, and the names of the variates in a given canonical set; (c) saves resultant output.

References

Nimon, K., Henson, R., & Gates, M. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and demonstration of canonical commonality analysis. Multivariate Behavioral Research, 45,702-724.

See Also

canonCommonality