ridge.reg: Ridge regression

In Compositional: Compositional Data Analysis

Ridge regression

Description

Ridge regression.

Usage

ridge.reg(y, x, lambda, B = 1, xnew = NULL)

Arguments

y	A real valued vector. If it contains percentages, the logit transformation is applied.
x	A matrix with the predictor variable(s), they have to be continuous.
lambda	The value of the regularisation parameter \lambda.
B	If B = 1 (default value) no bootstrpa is performed. Otherwise bootstrap standard errors are returned.
xnew	If you have new data whose response value you want to predict put it here, otherwise leave it as is.

Details

This is used in the function alfa.ridge. There is also a built-in function available from the MASS library, called "lm.ridge".

Value

A list including:

beta	The beta coefficients.
seb	The standard eror of the coefficiens. If B > 1 the bootstrap standard errors will be returned.
est	The fitted or the predicted values (if xnew is not NULL).

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail] and Giorgos Athineou <[e-mail]>.

References

Hoerl A.E. and R.W. Kennard (1970). Ridge regression: Biased estimation for nonorthogonal problems. Technometrics, 12(1): 55-67.

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

See Also

ridge.tune, alfa.ridge, ridge.plot

Examples

y <- as.vector(iris[, 1])
x <- as.matrix(iris[, 2:4])
mod1 <- ridge.reg(y, x, lambda = 0.1)
mod2 <- ridge.reg(y, x, lambda = 0)

Compositional documentation built on Oct. 9, 2024, 5:10 p.m.