Imputation by a weighted linear normal regression.

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`y` |
Incomplete data vector of length |

`ry` |
Vector of missing data pattern ( |

`x` |
Matrix ( |

`ridge` |
Ridge parameter in the diagonal of |

`imputationWeights` |
Optional vector of sampling weights |

`pls.facs` |
Number of factors in PLS regression (if used). The default is |

`interactions` |
Optional vector of variables for which interactions should be created |

`quadratics` |
Optional vector of variables which should also be included as quadratic effects. |

`...` |
Further arguments to be passed |

A vector of length `nmis=sum(!ry)`

with imputed values.

Alexander Robitzsch

For examples see `mice.impute.weighted.pmm`

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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