Orthogonal Least Squares for forward Selection

Version 1.0.0 (2.36 KB) by Shayan Sepahvand
This function allows the user to determine more important regressors in least squares method.
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Updated 3 Jan 2019

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The attached function inputs number of data samples, noise variance and polynomial coefficient vector to estimate the parameters using subset selection.

Cite As

Shayan Sepahvand (2024). Orthogonal Least Squares for forward Selection (https://www.mathworks.com/matlabcentral/fileexchange/69887-orthogonal-least-squares-for-forward-selection), MATLAB Central File Exchange. Retrieved .

O. Nelles, Nonlinear System Identification, Springer-Verlag Berlin Heidelberg 2001

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0