Reshaped Sequential Replacement Toolbox
The Reshaped Sequential Replacement Toolbox for MATLAB is a collection of MATLAB modules for carrying out variable selection based on the Reshaped Sequential Replacement (RSR) algorithm. The RSR algorithm can be used both in regression and classification. The implemented methods are Ordinary Least Squares (OLS) (sometimes called Multiple Linear Regression - MLR) and Principal Component Regression (PCR) in regression and K Nearest Neighbours (kNN) in classification. A pseudo-graphical user interface (p-gui), which assists loading the data, creating the options and launching the calculation, is also provided with the toolbox.
 Help files
HTML files are provided toghter with the MATLAB files in order to help the user. The full help is also available on line. The HTML help provides some underlying information on variable selection (see Theory section); it also explains how to prepare your data, how to create the options and how to launch the variable selection algorithm.
 Conditions and warranty
The toolbox is freeware and may be used (but not modified) if proper reference is given to the authors. Preferably refer to the followign papers:

Cassotti, M., Grisoni, F., Todeschini, R. (2014). Reshaped Sequential Replacement: an efficient approach to variable selection. Chemometrics and Intelligent Laboratory Systems, 133, 136-148. doi: 10.1016/j.chemolab.2014.01.011

Grisoni, F., Cassotti, M., Todeschini, R. (2014). Reshaped Sequential Replacement for variable selection in QSPR: comparison with other reference methods. Journal of Chemometrics, 28, 249-259. doi: 10.1002/cem.2603

In short, no guarantees, whatsoever, are given for the quality of this toolbox or for the consequences of its use. It is inevitable that there will be some bugs, but we have tried to test the algorithms thoroughly.

You can freely download the MATLAB modules:

download Reshaped Sequential Replacement Toolbox