chemometrics (version 1.4.4)

plotSEPmvr: Plot SEP from repeated DCV

Description

Generate plot showing SEP values for Repeated Double Cross Validation

Usage

plotSEPmvr(mvrdcvobj, optcomp, y, X, method = "simpls", complete = TRUE, ...)

Value

SEPdcv

all SEP values from repeated double-CV

SEPcv

SEP values from classical CV

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

complete

if TRUE the SEPcv values are drawn and computed for the same range of components as included in the mvrdcvobj object; if FALSE only optcomp components are computed and their results are displayed

...

additional plot arguments

Author

Peter Filzmoser <[e-mail]>

Details

After running repeated double-CV, this plot visualizes the distribution of the SEP 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)
plot1 <- plotSEPmvr(res,opt=7,y,X,method="simpls")