gen.ridge {mda} | R Documentation |
Perform a penalized regression, as used in penalized discriminant analysis.
gen.ridge(x, y, weights, lambda=1, omega, df, ...)
x y weights |
the x and y matrix and possibly a weight vector. |
lambda |
the shrinkage penalty coefficient. |
omega |
a penalty object; omega is the eigendecomposition of the penalty matrix, and need not have full rank. By default, standard ridge is used. |
df |
an alternative way to prescribe lambda, using the notion of equivalent degrees of freedom. |
A generalized ridge regression, where the coefficients are penalized according to omega. See the function definition for further details. No functions are provided for producing one dimensional penalty objects (omega).