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

This function calculates the significant multivariate correlation (`smc`

) metric for an `mvdareg`

object

1 | ```
smc(object, ncomps = object$ncomp, corrected = F)
``` |

`object` |
an mvdareg or mvdapaca object, i.e. |

`ncomps` |
the number of components to include in the model (see below). |

`corrected` |
whether there should be a correction of 1st order auto-correlation in the residuals. |

Note that hidden objects include the smc modeled matrix and error matrices

`smc`

is used to extract a summary of the significant multivariae correlation of a PLS model.

If `comps`

is missing (or is `NULL`

), summaries for all `smc`

estimates are returned. Otherwise, if comps are given parameters for a model with only the requested component comps is returned.

The output of `smc`

is an `smc summary`

detailing the following:

`smc` |
significant multivariate correlation statistic ( |

`p.value` |
p-value of the smc statistic. |

`f.value` |
f-value of the smc statistic. |

`Significant` |
Assessment of statistical significance. |

Nelson Lee Afanador ([email protected])

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 7 8 9 10 11 12 13 | ```
data(Penta)
mod1 <- plsFit(log.RAI ~., scale = TRUE, data = Penta[, -1],
ncomp = 2, validation = "loo")
smc(mod1)
plot(smc(mod1))
### PLS MODEL FIT WITH method = 'wrtpls' and validation = 'none', i.e. WRT-PLS is performed ###
## Not run:
mod2 <- plsFit(Sepal.Length ~., scale = TRUE, data = iris,
method = "wrtpls", validation = "none") #ncomp is ignored
plot(smc(mod2, ncomps = 2))
## End(Not run)
``` |

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