Generate plot showing trimmed SEP values for Repeated Double Cross Validation for Partial RObust MRegression (PRM)
1  plotSEPprm(prmdcvobj, optcomp, y, X, complete = TRUE, ...)

prmdcvobj 
object from repeated doubleCV of PRM, see 
optcomp 
optimal number of components 
y 
data from response variable 
X 
data with explanatory variables 
complete 
if TRUE the trimmed SEPcv values are drawn and computed from

... 
additional arguments ofr 
After running repeated doubleCV for PRM, this plot visualizes the distribution of the SEP values. While the gray lines represent the resulting trimmed SEP values from repreated double CV, the black line is the result for standard CV with PRM, and it is usually too optimistic.
SEPdcv 
all trimmed SEP values from repeated doubleCV 
SEPcv 
trimmed SEP values from usual 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.
prm
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 < prm_dcv(X,y,a=4,repl=2)
plot1 < plotSEPprm(res,opt=res$afinal,y,X)

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