Function ridge_fit 

pub fn ridge_fit(
    x: &Matrix,
    y: &[f64],
    options: &RidgeFitOptions,
) -> Result<RidgeFit>

Fits ridge regression for a single lambda value.

Arguments

• x - Design matrix (n × p). Should include intercept column if intercept=true.
• y - Response vector (n elements)
• options - Ridge fitting options

Returns

A RidgeFit containing the fit results.

Errors

Returns an error if:

• lambda < 0
• Dimensions don’t match
• Matrix is numerically singular

Algorithm

Uses the augmented QR approach:

1. Standardize X and center y (if requested)
2. Build augmented system:

   X_aug = [X_std; sqrt(lambda) * I_p]
   y_aug = [y_centered; 0_p]

3. Solve using QR decomposition
4. Unstandardize coefficients

Example

use linreg_core::linalg::Matrix;
use linreg_core::regularized::ridge::{ridge_fit, RidgeFitOptions};

let x = Matrix::new(3, 2, vec![
    1.0, 2.0,
    1.0, 3.0,
    1.0, 4.0,
]);
let y = vec![3.0, 5.0, 7.0];

let options = RidgeFitOptions {
    lambda: 1.0,
    intercept: true,
    standardize: true,
};

let fit = ridge_fit(&x, &y, &options).unwrap();
println!("Intercept: {}", fit.intercept);
println!("Coefficients: {:?}", fit.coefficients);