Weighted linear regression in pure Rust with only a single any 3rd party dependency (num-traits).
Forked to expose as a library crate & enable generic float support - the hard work was done by vspaz here: https://github.com/vspaz/wls-rs
Use in your project by adding this line to your Cargo.toml:
wls = {git = "https://github.com/fred314159265/wls-rs.git"}use wls::models::wls::Wls;
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();
println!("Slope: {:?}", point.get_slope());
println!("Intercept: {:?}", point.get_intercept());
}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 without special stats packages, such as Python statsmodels or Pandas.