Learn R Programming

chemometrics (version 1.4.4)

plotpredprm: Plot predictions from repeated DCV of PRM

Description

Generate plot showing predicted values for Repeated Double Cross Validation of Partial Robust M-regression

Usage

plotpredprm(prmdcvobj, optcomp, y, X, ...)

Value

A plot is generated.

Arguments

prmdcvobj

object from repeated double-CV of PRM, see prm_dcv

optcomp

optimal number of components

y

data from response variable

X

data with explanatory variables

...

additional plot arguments

Author

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

Details

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.

References

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

See Also

prm

Examples

Run this code
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)

Run the code above in your browser using DataLab