wls: Weighted Least Squares

In ipd: Inference on Predicted Data

Weighted Least Squares

Description

Computes the weighted least squares estimate of the coefficients.

Usage

wls(X, Y, w = NULL, return_se = FALSE)

Arguments

X	(matrix): n x p matrix of covariates.
Y	(vector): p-vector of outcome values.
w	(vector, optional): n-vector of sample weights.
return_se	(bool, optional): Whether to return the standard errors of the coefficients.

Value

(list): A list containing the following:

theta

(vector): p-vector of weighted least squares estimates of the coefficients.

se

(vector): If return_se == TRUE, return the p-vector of standard errors of the coefficients.

Examples

n <- 1000

X <- rnorm(n, 1, 1)

w <- rep(1, n)

Y <- X + rnorm(n, 0, 1)

wls(X, Y, w = w, return_se = TRUE)

ipd documentation built on April 4, 2025, 4:41 a.m.