| plotresprm | R Documentation | 
Generate plot showing residuals for Repeated Double Cross Validation for Partial Robust M-regression
plotresprm(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 residuals. 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.
prm
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)
plot4 <- plotresprm(res,opt=res$afinal,y,X)
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