Module regression 

Regression — ordinary least squares. Simple (one-predictor) linear regression with the full inferential output: coefficients, R², residual standard error, and real t-based standard errors / p-values from the distributions library (no placeholder significance).

Multiple linear regression (the normal-equations / QR solve over solvers::linear_algebra) is the natural next module here; simple OLS is a complete capability on its own and is what the domain libs need first.

Structs

LinearRegression

Ordinary-least-squares fit of y = intercept + slope·x.

Functions

simple_linear_regression

Simple linear regression of y on x. None if the lengths differ, n < 3 (need n−2 ≥ 1 residual degrees of freedom for inference), or x has zero variance (slope undefined).