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

Robust PLS by partial robust M-regression.

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`X` |
predictor matrix |

`y` |
response variable |

`a` |
number of PLS components |

`fairct` |
tuning constant, by default fairct=4 |

`opt` |
if "l1m" the mean centering is done by the l1-median, otherwise if "median" the coordinate-wise median is taken |

`usesvd` |
if TRUE, SVD will be used if X has more columns than rows |

M-regression is used to robustify PLS, with initial weights based on the FAIR weight function.

`coef` |
vector with regression coefficients |

`intercept` |
coefficient for intercept |

`wy` |
vector of length(y) with residual weights |

`wt` |
vector of length(y) with weights for leverage |

`w` |
overall weights |

`scores` |
matrix with PLS X-scores |

`loadings` |
matrix with PLS X-loadings |

`fitted.values` |
vector with fitted y-values |

`mx` |
column means of X |

`my` |
mean of y |

Peter Filzmoser <[email protected]>

S. Serneels, C. Croux, P. Filzmoser, and P.J. Van Espen. Partial robust M-regression. Chemometrics and Intelligent Laboratory Systems, Vol. 79(1-2), pp. 55-64, 2005.

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