Component plot for repeated DCV of PRM

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Description

Generate plot showing optimal number of components for Repeated Double Cross-Validation of Partial Robust M-regression

Usage

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plotcompprm(prmdcvobj, ...)

Arguments

prmdcvobj

object from repeated double-CV of PRM, see prm_dcv

...

additional plot arguments

Details

After running repeated double-CV for PRM, this plot helps to decide on the final number of components.

Value

optcomp

optimal number of components

compdistrib

frequencies for the optimal number of components

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

References

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

See Also

prm

Examples

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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)
plot2 <- plotcompprm(res)

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