Linear functions are fundamental building blocks in mathematics and play a key role in solving real-world problems where the rate of change remains constant. Linear functions arise in a wide range of ...

About This project implements linear regression end-to-end in R using a dataset with 30 predictors. It shows how to build an ordinary least squares (OLS) estimator without using lm (), compute ...

The objective of this notebook is to compare the methodologies used in linear regression: traditional statistical techniques versus machine learning optimization methods, such as gradient descent.

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 30, No. 2 (1981), pp. 125-131 (7 pages) In generalized linear models each observation is linked with a predicted value ...

This is a preview. Log in through your library . Abstract Many data are suitably modeled by functions consisting of straight-line segments. These functions may be called piecewise-linear. Smooth ...