lm.ridge
From MASS v7.345
by Brian Ripley
Ridge Regression
Fit a linear model by ridge regression.
 Keywords
 models
Usage
lm.ridge(formula, data, subset, na.action, lambda = 0, model = FALSE, x = FALSE, y = FALSE, contrasts = NULL, ...)
Arguments
 formula

a formula expression as for regression models, of the form
response ~ predictors
. See the documentation offormula
for other details.offset
terms are allowed.  data

an optional data frame in which to interpret the variables occurring
in
formula
.  subset
 expression saying which subset of the rows of the data should be used in the fit. All observations are included by default.
 na.action
 a function to filter missing data.
 lambda
 A scalar or vector of ridge constants.
 model
 should the model frame be returned? Not implemented.
 x
 should the design matrix be returned? Not implemented.
 y
 should the response be returned? Not implemented.
 contrasts

a list of contrasts to be used for some or all of factor terms in the
formula. See the
contrasts.arg
ofmodel.matrix.default
.  ...

additional arguments to
lm.fit
.
Details
If an intercept is present in the model, its coefficient is not penalized. (If you want to penalize an intercept, put in your own constant term and remove the intercept.)
Value

A list with components
 coef

matrix of coefficients, one row for each value of
lambda
. Note that these are not on the original scale and are for use by thecoef
method.  scales
 scalings used on the X matrix.
 Inter
 was intercept included?
 lambda
 vector of lambda values
 ym

mean of
y
 xm

column means of
x
matrix  GCV
 vector of GCV values
 kHKB
 HKB estimate of the ridge constant.
 kLW
 LW estimate of the ridge constant.
References
Brown, P. J. (1994) Measurement, Regression and Calibration Oxford.
See Also
Examples
library(MASS)
longley # not the same as the SPLUS dataset
names(longley)[1] < "y"
lm.ridge(y ~ ., longley)
plot(lm.ridge(y ~ ., longley,
lambda = seq(0,0.1,0.001)))
select(lm.ridge(y ~ ., longley,
lambda = seq(0,0.1,0.0001)))
Community examples
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