This function peforms a 1st order test of the Residual Significant Multivariate Correlation Matrix in order to help determine if the `smc`

should be performed correcting for 1st order autocorrelation.

1 | ```
smc.acfTest(object, ncomp = object$ncomp)
``` |

`object` |
an object of class |

`ncomp` |
the number of components to include in the acf assessment |

This function computes a test for 1st order auto correlation in the `smc`

residual matrix.

The output of `smc.acfTest`

is a list detailing the following:

`variable` |
variable for whom the test is being performed |

`ACF` |
value of the 1st lag of the ACF |

`Significant` |
Assessment of the statistical significance of the 1st order lag |

Nelson Lee Afanador (nelson.afanador@mvdalab.com)

Thanh N. Tran, Nelson Lee Afanador, Lutgarde M.C. Buydens, Lionel Blanchet, Interpretation of variable importance in Partial Least Squares with Significance Multivariate Correlation (sMC). Chemom. Intell. Lab. Syst. 2014; 138: 153:160.

Nelson Lee Afanador, Thanh N. Tran, Lionel Blanchet, Lutgarde M.C. Buydens, Variable importance in PLS in the presence of autocorrelated data - Case studies in manufacturing processes. Chemom. Intell. Lab. Syst. 2014; 139: 139:145.

1 2 3 4 5 6 |

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

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.