ridgeCV: Repeated CV for Ridge regression

In chemometrics: Multivariate Statistical Analysis in Chemometrics

Repeated CV for Ridge regression

Description

Performs repeated cross-validation (CV) to evaluate the result of Ridge regression where the optimal Ridge parameter lambda was chosen on a fast evaluation scheme.

Usage

ridgeCV(formula, data, lambdaopt, repl = 5, segments = 10, 
   segment.type = c("random", "consecutive", "interleaved"), length.seg, 
   trace = FALSE, plot.opt = TRUE, ...)

Arguments

formula	formula, like y~X, i.e., dependent~response variables
data	data frame to be analyzed
lambdaopt	optimal Ridge parameter lambda
repl	number of replications for the CV
segments	the number of segments to use for CV, or a list with segments (see mvrCv)
segment.type	the type of segments to use. Ignored if 'segments' is a list
length.seg	Positive integer. The length of the segments to use. If specified, it overrides 'segments' unless 'segments' is a list
trace	logical; if 'TRUE', the segment number is printed for each segment
plot.opt	if TRUE a plot will be generated that shows the predicted versus the observed y-values
...	additional plot arguments

Details

Generalized Cross Validation (GCV) is used by the function lm.ridge to get a quick answer for the optimal Ridge parameter. This function should make a careful evaluation once the optimal parameter lambda has been selected. Measures for the prediction quality are computed and optionally plots are shown.

Value

residuals	matrix of size length(y) x repl with residuals
predicted	matrix of size length(y) x repl with predicted values
SEP	Standard Error of Prediction computed for each column of "residuals"
SEPm	mean SEP value
sMAD	MAD of Prediction computed for each column of "residuals"
sMADm	mean of MAD values
RMSEP	Root MSEP value computed for each column of "residuals"
RMSEPm	mean RMSEP value

Author(s)

Peter Filzmoser <[e-mail]>

References

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

See Also

lm.ridge, plotRidge

Examples

data(PAC)
res=ridgeCV(y~X,data=PAC,lambdaopt=4.3,repl=5,segments=5)

chemometrics documentation built on Aug. 25, 2023, 5:18 p.m.