Description Usage Arguments Value

`macor`

generalizes `acor`

to the case of more than two data
domains.

1 |

`x` |
a list of numeric matrices which contain the data from the different domains |

`coef` |
a list of matrices containing the canonical vectors related to each data domain. Each matrix contains the respective canonical vectors as its columns. |

`center` |
a list of logical values indicating whether the empirical mean
of (each column of) the corresponding data matrix should be subtracted.
Alternatively, a list of vectors can be supplied, where each vector
specifies the mean to be subtracted from the corresponding data matrix.
Each list element is passed to |

`scale_` |
a list of logical values indicating whether the columns of the
corresponding data matrix should be scaled to have unit variance before the
analysis takes place. The default is |

`macor`

returns a list of class `mcancor`

with the
following elements:

`cor` |
a multi-dimensional array containing the additional correlations explained by each pair of canonical variables. The first two dimensions correspond to the domains, and the third dimension corresponds to the different canonical variables per domain. |

`coef` |
copied from the input arguments |

`center` |
the list of empirical means used to center the data matrices |

`scale` |
the list of empirical standard deviations used to scale the data matrices |

`xp` |
the
list of deflated data matrices corresponding to |

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