R: Plot predictions from repeated DCV of PRM

plotpredprm {chemometrics} | R Documentation

## 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, ...)

### 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

### 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.

### Value

A plot is generated.

### 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

    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)

[Package chemometrics version 1.4.2 Index]