Total Least Squares Method

Mathematical method known as total least squares or orthogonal regression or error-in-variables.
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Updated 11 Apr 2013

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We present a Matlab toolbox which can solve basic problems related to the Total Least Squares (TLS) method in the modeling. By illustrative examples we show how to use the TLS method for solution of:
- linear regression model
- nonlinear regression model
- fitting data in 3D space
- identification of dynamical system

This toolbox requires another two functions, which are already published in Matlab Central File Exchange. Those functions will be installed to computer via supporting install package 'requireFEXpackage' included in TLS package. For more details see ReadMe.txt file.

Authors: Ivo Petras, Dagmar Bednarova, Tomas Skovranek, and Igor Podlubny
(Technical University of Kosice, Slovakia)

Detailed description of the functions, examples and demos can be found at the link:

Ivo Petras and Dagmar Bednarova: Total Least Squares Approach to Modeling: A Matlab Toolbox, Acta Montanistica Slovaca, vol. 15, no. 2, 2010, pp. 158-170.
(http://actamont.tuke.sk/pdf/2010/n2/8petras.pdf)

Cite As

Ivo Petras (2024). Total Least Squares Method (https://www.mathworks.com/matlabcentral/fileexchange/31109-total-least-squares-method), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.2.0.0

Fixed bug discovered by Martin and Alex.

1.1.0.0

Updated function orm(). Fixed error discovered by 'Trison'.

1.0.0.0