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)
#> $theta
#> X
#> 0.9892422
#>
#> $se
#> X
#> 0.0226202
#>