Generate plot showing SEP values for Repeated Double Cross Validation
1  plotSEPmvr(mvrdcvobj, optcomp, y, X, method = "simpls", complete = TRUE, ...)

mvrdcvobj 
object from repeated doubleCV, see 
optcomp 
optimal number of components 
y 
data from response variable 
X 
data with explanatory variables 
method 
the multivariate regression method to be used, see

complete 
if TRUE the SEPcv values are drawn and computed for the same range of components as included in the mvrdcvobj object; if FALSE only optcomp components are computed and their results are displayed 
... 
additional plot arguments 
After running repeated doubleCV, this plot visualizes the distribution of the SEP values.
SEPdcv 
all SEP values from repeated doubleCV 
SEPcv 
SEP values from classical CV 
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.
1 2 3 4 5 6  data(NIR)
X < NIR$xNIR[1:30,] # first 30 observations  for illustration
y < NIR$yGlcEtOH[1:30,1] # only variable Glucose
NIR.Glc < data.frame(X=X, y=y)
res < mvr_dcv(y~.,data=NIR.Glc,ncomp=10,method="simpls",repl=10)
plot1 < plotSEPmvr(res,opt=7,y,X,method="simpls")

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