The predicted values and the residuals are shown for robust PLS using the optimal number of components.

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`prmobj` |
resulting object from CV of robust PLS, see |

`y` |
vector with values of response variable |

`...` |
additional plot arguments |

Robust PLS based on partial robust M-regression is available at `prm`

.
Here the function `prm_cv`

has to be used first, applying cross-validation
with robust PLS. Then the result is taken by this routine and two plots are generated
for the optimal number of PLS components: The measured versus the predicted y, and
the predicted y versus the residuals.

A plot is generated.

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

`prm`

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