linear_gd_optim: Linear Gradient Descend

In FedericoCortese/R4DScm:

Description

This function computes the vector of parameters in a linear regression model via the Gradient Descend Method.

Usage

linear_gd_optim(b_pre, X, y, tol = 0.001, maxit = 1000, stepsize = 0.001)

Arguments

b_pre	vector of initial parameters
X	Covariates Matrix: each column contains observations for each covariate.
y	Response variable observations
tol	Tolerance level for the optimization process, the default is 0.001.
maxit	Maximum iterations number
stepsize	The value for the stepsize in the equation of the gradient descend

Value

A list containing the fitted values for the beta vector and the number of iterations performed

Examples

set.seed(8675309)
n = 1000
x1 = rnorm(n)
x2 = rnorm(n)
y = 1 + .5*x1 + .2*x2 + rnorm(n)
X=cbind(x1,x2)
b_pre=c(0,0,0)
linear_gd_optim(b_pre,X,y)

FedericoCortese/R4DScm documentation built on July 12, 2021, 5:30 a.m.