Linear regression with the Gauss-Seidel Solver

This function implements linear regression by solving the normal equations. It constructs matrices X'X and X'Y and solves for beta in X'X*beta=X'Y using the iterative Gauss-Seidel solver of system of linear equations.

linreg.gs(Y, X)

Arguments

Y	vector of outcome variable
X	matrix of covariates

Value

coefs vector of coefficients

Examples

linreg.sor(women$height,women$weight)
#> $coefs
#> [1] 25.7246016  0.2872409
#>