Description Usage Arguments Details Value Examples

cross-validated method to evaluate the fit of "msma".

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 |

`X` |
a (list of) matrix, explanatory variable(s). |

`Y` |
a (list of) matrix, objective variable(s). |

`Z` |
a (list of) matrix, response variable(s). |

`comp` |
numeric scalar for the maximum number of componets to be considered. |

`lambdaX` |
numeric vector of regularized parameters for X with length equal to the number of blocks. If omitted, no regularization is conducted. |

`lambdaY` |
numeric vector of regularized parameters for Y with length equal to the number of blocks. If omitted, no regularization is conducted. |

`lambdaXsup` |
numeric vector of regularized parameters for the super weight of X with length equal to the number of blocks. If omitted, no regularization is conducted. |

`lambdaYsup` |
numeric vector of regularized parameters for the super weight of Y with length equal to the number of blocks. If omitted, no regularization is conducted. |

`eta` |
numeric scalar the parameter indexing the penalty family. |

`type` |
a character. |

`inX` |
a (list of) numeric vector to specify the variables of X which are always in the model. |

`inY` |
a (list of) numeric vector to specify the variables of X which are always in the model. |

`inXsup` |
a (list of) numeric vector to specify the blocks of X which are always in the model. |

`inYsup` |
a (list of) numeric vector to specify the blocks of Y which are always in the model. |

`muX` |
a numeric scalar for the weight of X for the supervised. |

`muY` |
a numeric scalar for the weight of Y for the supervised. |

`nfold` |
number of folds - default is 5. |

`seed` |
number of seed for the random number. |

`intseed` |
seed number for the random number in the parameter estimation algorithm. |

k-fold cross-validation for `msma`

`err` |
The mean cross-validated errors which has three elements consisting of the mean of errors for X and Y, the errors for X and for Y. |

1 2 3 4 5 6 7 8 9 10 11 | ```
##### data #####
tmpdata = simdata(n = 50, rho = 0.8, Yps = c(10, 12, 15), Xps = 20, seed=1)
X = tmpdata$X; Y = tmpdata$Y
##### One Component CV #####
cv1 = cvmsma(X, Y, comp = 1, lambdaX=2, lambdaY=1:3, nfold=5, seed=1)
cv1
##### Two Component CV #####
cv2 = cvmsma(X, Y, comp = 2, lambdaX=2, lambdaY=1:3, nfold=5, seed=1)
cv2
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.