vcov: Variance-Covariance Matrix for Fitted Ridge Model

In lmridge: Linear Ridge Regression with Ridge Penalty and Ridge Statistics

Variance-Covariance Matrix for Fitted Ridge Model

Description

The vcov function computes the variance-covariance matrix for the estimates of linear ridge regression model.

Usage

## S3 method for class 'lmridge'
vcov(object, ...)

Arguments

object	For VCOV method, an object of class "lmridge", i.e., a fitted model.
...	Not presently used in this implementation.

Details

The vcov function computes variance-covariance matrix for scalar or vector value of biasing parameter K provided as argument to lmridge function.

Value

A list of matrix of estimated covariances in the linear ridge regression model for scalar or vector biasing parameter KK is produced. Each list element has row and column names corresponding to the parameter names given by the coef(mod). List items are named correspond to values of biasing parameter K.

Note

Covariance will be without intercept term, as intercept term is not penalized in ridge regression.

Author(s)

Muhammad Imdad Ullah, Muhammad Aslam

References

Brown, G.W. and Beattie, B.R. (1975). Improving Estimates of Economic Parameters by use of Ridge Regression with Production Function Applications. American Journal of Agricultural Economics, 57(1), 21-32. doi: 10.2307/1238836.

See Also

The ridge model fitting lmridge, ridge VIF values vif

Examples

data(Hald)
mod<- lmridge(y~., data=as.data.frame(Hald), scaling="sc", K=seq(0,1,.2) )

vcov.lmridge(mod)
vcov(mod)

lmridge documentation built on Jan. 15, 2023, 5:06 p.m.