Module regression 

Regression analysis.

Simple and multiple linear regression with OLS, R², coefficient testing, ANOVA, VIF, and residual diagnostics.

Examples

use u_analytics::regression::simple_linear_regression;

let x = [1.0, 2.0, 3.0, 4.0, 5.0];
let y = [2.1, 3.9, 6.1, 7.9, 10.1];
let result = simple_linear_regression(&x, &y).unwrap();
assert!((result.slope - 2.0).abs() < 0.1);
assert!((result.intercept - 0.1).abs() < 0.2);
assert!(result.r_squared > 0.99);

Structs

MultipleRegressionResult

Result of a multiple linear regression: y = Xβ + ε.

SimpleRegressionResult

Result of a simple linear regression: y = intercept + slope · x.

Functions

multiple_linear_regression

Computes multiple linear regression via OLS (Cholesky solve).

predict_multiple

Predicts y values given new predictor data and a multiple regression result.

predict_simple

Predicts y values given new x data and a simple regression result.

simple_linear_regression

Computes simple linear regression (OLS closed-form).