Regression toolbox for MATLAB

The Regression toolbox for MATLAB is a collection of MATLAB modules for calculating regression multivariate models: Ordinary Least Squares (OLS), Partial Least Squares (PLS), Principal Component Regression (PCR), Ridge regression, local regression based on K Nearest Neighbours (KNN) and Binned Nearest Neighbours (BNN) approaches, and variable selection approaches (All Subset Models, Forward selection, Genetic Algorithms and Reshaped Sequential Replacement). Help files HTML files are provided toghter with the MATLAB files in order to help the user. The HTML help provides some underlying information on multivariate regression (see Theory section); it also explains how to prepare your data, how to handle the model settings and how to calculate the regression models. An example of analysis is shown. Conditions and warranty The toolbox is freeware and may be used if proper reference is given to the authors. Please, refer to the following paper: V. Consonni, G. Baccolo, F. Gosetti, R. Todeschini, D. Ballabio (2021) A MATLAB toolbox for multivariate regression coupled with variable selection. Chemometrics and Intelligent Laboratory Systems, 213, 104313 [link] The Regression toolbox for MATLAB is distributed with an Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence