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

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.

1 | ```
canonVariate(A, B, nofns)
``` |

`A` |
Matrix containing variable set A |

`B` |
Matrix containing variable set B |

`nofns ` |
Number of canonical functions to analyze |

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.

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.

This function is internal to `canonCommonality`

,
called during runtime and passed the appropriate parameters.
This is not an end-user function.

Kim Nimon <[email protected]>

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.

yhat documentation built on May 29, 2017, 10:39 p.m.

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