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.

This software is also referenced in ORMS.

References in zbMATH (referenced in 235 articles , 1 standard article )

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  1. Mahboubi, Assia; Melquiond, Guillaume; Sibut-Pinote, Thomas: Formally verified approximations of definite integrals (2019)
  2. Peña, Juan Manuel; Sauer, Tomas: SVD update methods for large matrices and applications (2019)
  3. Wang, Lizhi; Nikouei Mehr, Maryam: An optimization approach to epistasis detection (2019)
  4. Yang, Lihong; Chen, Zhong; Xie, Kechao: An efficient method for approximate solution of a singular integral equation with Cauchy kernel (2019)
  5. Deschner, Stephan C.; Illenseer, Tobias F.; Duschl, Wolfgang J.: Self-similar solutions to isothermal shock problems (2018)
  6. Díaz-Alvarado, Felipe A.; Miranda-Pérez, Jenny; Grossmann, Ignacio E.: Search for reaction pathways with P-graphs and reaction blocks: methanation of carbon dioxide with hydrogen (2018)
  7. Fortunati, Alessandro; Wiggins, Stephen: Transient invariant and quasi-invariant structures in an example of an aperiodically time dependent fluid flow (2018)
  8. Himpe, Christian; Leibner, Tobias; Rave, Stephan: Hierarchical approximate proper orthogonal decomposition (2018)
  9. Johnson, Robert W.: Algorithm 988. AMGKQ: an efficient implementation of adaptive multivariate Gauss-Kronrod quadrature for simultaneous integrands in Octave/MATLAB (2018)
  10. Karl Sjöstrand; Line Clemmensen; Rasmus Larsen; Gudmundur Einarsson; Bjarne Ersbøll: SpaSM: A MATLAB Toolbox for Sparse Statistical Modeling (2018) not zbMATH
  11. Manish Sreenivasa; Monika Harant: ModelFactory: A Matlab/Octave based toolbox to create human body models (2018) arXiv
  12. Nasti, Lucia; Milazzo, Paolo: A hybrid automata model of social networking addiction (2018)
  13. Nomura, Seiichi: C programming and numerical analysis: an introduction (2018)
  14. Sanderson, Conrad; Curtin, Ryan: A user-friendly hybrid sparse matrix class in C++ (2018)
  15. Smith, David J.: A nearest-neighbour discretisation of the regularized stokeslet boundary integral equation (2018)
  16. Weiser, Martin; Freytag, Yvonne; Erdmann, Bodo; Hubig, Michael; Mall, Gita: Optimal design of experiments for estimating the time of death in forensic medicine (2018)
  17. Wei, Yimin; Stanimirović, Predrag; Petković, Marko: Numerical and symbolic computations of generalized inverses (2018)
  18. Yan, Ada W. C.; Black, Andrew J.; McCaw, James M.; Rebuli, Nicolas; Ross, Joshua V.; Swan, Annalisa J.; Hickson, Roslyn I.: The distribution of the time taken for an epidemic to spread between two communities (2018)
  19. Adriano Zambom and Michael Akritas: NonpModelCheck: An R Package for Nonparametric Lack-of-Fit Testing and Variable Selection (2017) not zbMATH
  20. Batselier, Kim; Wong, Ngai: Inverse multivariate polynomial root-finding: numerical implementations of the affine and projective Buchberger-Möller algorithm (2017)

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