GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab. It may also be used as a batch-oriented language.

Octave has extensive tools for solving common numerical linear algebra problems, finding the roots of nonlinear equations, integrating ordinary functions, manipulating polynomials, and integrating ordinary differential and differential-algebraic equations. It is easily extensible and customizable via user-defined functions written in Octave's own language, or using dynamically loaded modules written in C++, C, Fortran, or other languages.

GNU Octave is also freely redistributable software. You may redistribute it and/or modify it under the terms of the GNU General Public License (GPL) as published by the Free Software Foundation.

The main author and father of Octave is John W. Eaton and by now many other make substantial contributions. Since Octave is free software you are encouraged to help make Octave more useful by writing and contributing additional functions for it, and by reporting any problems you might stumble across.

• On most Linux distributions Octave is included as a package, on some distributions OctaveForge is also included. If not it is advisable to download the package from www.Octave.org and compile/install it on your computer.
• For other systems consult the Octave Wiki.
• The host GNU Octave packages provides a newer, extensive collection of Octave packages. It is advisable to install some of these additions.
• The host SourceForge provides a selection of additional packages. It is advisable to install some of these additions.
• At Discourse find an active group with discussions and help about Octave.

• Table of Contents of the book by Springer.
• These are the Codes.tar for the book as a single file or in compressed form Codes.tgz
• Here there will be a (hopefully short) list of errors.

• A command for general linear regression is available at LinearRegression.m. This code is contained in the optim package for Octave.
  A version for Matlab is available at LinearRegression.m.
• A command for hypothesis testing with a binomial ditribution is given by binotest.m. This code is contained in the statistics package for Octave.
  A version for Matlab is available at binotest.m.
• There are two GUIs to use linear (FitTool.m) or nonlinear (FitToolNL.m) regression. Find some documentation in (CurveFit.pdf).
• There is an (old) Matlab version of a good code for nonlinear regression. The basic code is leasqr.m with the helper routine dfdp.m. Both code are not written by me. The demo code leasqrDemo.m provides sample calls.
• Two codes to use a Tikhonov regularization to approximate data or functions by smooth functions are available: for problems with one independent variable use regularization.m and for problems with two independent variables use regularization2D.m. An extensive documentation with examples, description of the algorithm and the mathematical background is available at RegularizationReport.pdf. These codes are contained in the splines package for Octave.
• FEMoctave is a simple finite element package. Find the documentation and the current version in FEMoctave-v.2.1.4.tar.gz. The package is also on github.com/AndreasStahel/FEMoctave.

• At the Octave Conference in Milano in June of 2013 I gave a short presentation (OctConf2013) on how Octave was used at the the Bern University of Applied Sciences.
• At the Octave Conference in Geneva on March 20-22, 2017 I presented a simple application of Octave being used to develop 16bit code for micro controllers. Find the slides and codes in the compressed file OctConf2017.tgz.

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January 1, 2022 by Andreas.Stahel@gmx.com