chemometrics (version 1.4.2)

plotpredmvr: Plot predictions from repeated DCV

Description

Generate plot showing predicted values for Repeated Double Cross Validation

Usage

plotpredmvr(mvrdcvobj, optcomp, y, X, method = "simpls", ...)

Value

A plot is generated.

Arguments

mvrdcvobj

object from repeated double-CV, see mvr_dcv

optcomp

optimal number of components

y

data from response variable

X

data with explanatory variables

method

the multivariate regression method to be used, see mvr

...

additional plot arguments

Author

Peter Filzmoser <[e-mail]>

Details

After running repeated double-CV, this plot visualizes the predicted values.

References

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

See Also

mvr

Examples

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 <- mvr_dcv(y~.,data=NIR.Glc,ncomp=10,method="simpls",repl=10)
plot3 <- plotpredmvr(res,opt=7,y,X,method="simpls")

Run the code above in your browser using DataCamp Workspace