Plot SEP from repeated DCV
Generate plot showing SEP values for Repeated Double Cross Validation
plotSEPmvr(mvrdcvobj, optcomp, y, X, method = "simpls", complete = TRUE, ...)
mvrdcvobj |
object from repeated double-CV, 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 double-CV, this plot visualizes the distribution of the SEP values.
SEPdcv |
all SEP values from repeated double-CV |
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.
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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