Plot predictions from repeated DCV of PRM
Generate plot showing predicted values for Repeated Double Cross Validation of Partial Robust M-regression
plotpredprm(prmdcvobj, optcomp, y, X, ...)
prmdcvobj |
object from repeated double-CV of PRM, see |
optcomp |
optimal number of components |
y |
data from response variable |
X |
data with explanatory variables |
... |
additional plot arguments |
After running repeated double-CV for PRM, this plot visualizes the predicted values. The result is compared with predicted values obtained via usual CV of PRM.
A plot is generated.
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 <- prm_dcv(X,y,a=4,repl=2) plot3 <- plotpredprm(res,opt=res$afinal,y,X)
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