Two plots from Ridge regression are generated: The MSE resulting from
Generalized Cross Validation (GCV) versus the Ridge parameter lambda,
and the regression coefficients versus lambda. The optimal choice for
lambda is indicated.
Usage
plotRidge(formula, data, lambda = seq(0.5, 50, by = 0.05), ...)
Arguments
formula
formula, like y~X, i.e., dependent~response variables
data
data frame to be analyzed
lambda
possible values for the Ridge parameter to evaluate
...
additional plot arguments
Value
Details
For all values provided in lambda the results for Ridge regression are computed.
The function lm.ridge is used for cross-validation and
Ridge regression.
References
K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical
Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.