lm.ridge {MASS}R Documentation

Ridge Regression


Fit a linear model by ridge regression.


lm.ridge(formula, data, subset, na.action, lambda = 0, model = FALSE,
         x = FALSE, y = FALSE, contrasts = NULL, ...)


formula a formula expression as for regression models, of the form response ~ predictors. See the documentation of formula 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?
x should the design matrix be returned?
y should the response be returned?
contrasts a list of contrasts to be used for some or all of factor terms in the formula. See the contrasts.arg of model.matrix.default.
... additional arguments to lm.fit.


If an intercept is present in the model, its coefficient is not penalized. (If you want to penalized an intercept, put in your own constant term and remove the intercept.)


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 the coef 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 L-W estimate of the ridge constant.


Brown, P. J. (1994) Measurement, Regression and Calibration Oxford.

See Also



data(longley) # not the same as the S-PLUS 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)))

[Package MASS version 7.2-23 Index]