This function carries out the canonical correlation analysis between a scalar variable and a list of mixed scalar and functional variables. There are four choices of the returned values and three representation methods of the functional variables.

1 2 |

`xL1` |
The mixed scalar and functional variables. For any number and any type of variables, |

`xL2` |
Same as |

`method` |
The representative methods for the functional coefficients. The method could be one of the 'basis', 'gq' and 'raw' for basis function expression, Gaussian quadrature and representative data points, respectively. |

`centre` |
Logic argument. Default is |

`tol` |
The threshold to decide whether the correlation is to small to be non-zero. |

`Control1` |
List of elements that controls the details of the functional coefficients for |

`Control2` |
Similar to |

`alpha` |
Candidate tuning parameters for the smoothness of the functional coefficients. |

Note that the smoothing parameters for both groups of variables are assumed to be the same. This is due to high computational cost of cross validation. See the example in `fccaXX`

.

`cor` |
A vector of the first canonical correlation. Each element of the vector is corresponding to one of the candidate tuning parameters. |

`alpha` |
The corresponding tuning parameters. |

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