R: Penalized Regression

gen.ridge {mda} | R Documentation

## Penalized Regression

### Description

Perform a penalized regression, as used in penalized discriminant analysis.

### Usage

    gen.ridge(x, y, weights, lambda=1, omega, df, ...)

### Arguments

`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.
`...` | currently not used.

### Value

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). `laplacian()` creates a two-dimensional penalty object, suitable for (small) images.

### See Also

`laplacian`

[Package mda version 0.4-10 Index]