
lm.ridge  Ridge Regression  Description Fit a linear model by ridge regression.  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 of formula for other details. offset terms are allowed.  
 
data  an optional data frame, list or environment 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 of model.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 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.  

 References Brown, P. J. (1994) Measurement, Regression and Calibration Oxford.  See Also lm  Examples 
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)))


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