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