weighted linear regression in pure Rust w/o any 3d party dependencies or frameworks.
mod models;
mod asserts;
use crate::models::wls::Wls;
use crate::asserts::asserts::assert_almost_equal;
fn main() {
let x_points = vec![1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0];
let y_points = vec![1.0, 3.0, 4.0, 5.0, 2.0, 3.0, 4.0];
let weights = vec![10.0, 1.0, 3.0, 8.0, 14.0, 21.0, 13.0];
let wls = Wls::new(x_points, y_points, Some(weights));
let point = wls.fit_linear_regression().unwrap();
assert_almost_equal(1.410964913,point.get_intercept(), 1.0e-6);
assert_almost_equal(0.321271930, point.get_slope(), 1.0e-6);
}WLS is based on the OLS method and help solve problems of model inadequacy or violations of the basic regression assumptions.
Estimating a linear regression with WLS is useful, but can appear to be daunting w/o special stats packages, such as Python statsmodels or Pandas.