GAUSS is a matrix programming language for mathematics and statistics, developed and marketed by Aptech Systems. Its primary purpose is the solution of numerical problems in statistics, econometrics, time-series, optimization and 2D- and 3D-visualization.[1] It was first written in 1980[2] and was first published in 1984 for MS-DOS.[3] It has since become available for Linux, macOS and Windows.[4]
Examples
- GAUSS has several application modules as well as functions in its runtime library (i.e., functions that come with GAUSS without extra cost):[5]
- Qprog – Quadratic programming
- SqpSolvemt – Sequential quadratic programming
- QNewton – Quasi-Newton unconstrained optimization
- EQsolve – Nonlinear equations solver
GAUSS Applications
A range of toolboxes are available for GAUSS at additional cost.[6]
| Toolbox | Description |
|---|---|
| Algorithmic Derivatives | A program for generating GAUSS procedures for computing algorithmic derivatives. |
| Constrained Maximum Likelihood MT | Solves the general maximum likelihood problem subject to general constraints on the parameters. |
| Constrained Optimization | Solves the nonlinear programming problem subject to general constraints on the parameters. |
| CurveFit | Nonlinear curve fitting. |
| Descriptive Statistics | Basic sample statistics including means, frequencies and crosstabs. This application is backwards compatible with programs written with Descriptive Statistics 3.1. |
| Descriptive Statistics MT | Basic sample statistics including means, frequencies and crosstabs. This application is thread-safe and takes advantage of structures. |
| Discrete Choice | A statistical package for estimating discrete choice and other models in which the dependent variable is qualitative in some way. |
| FANPAC MT | Comprehensive suite of GARCH (Generalized AutoRegressive Conditional Heteroskedastic) models for estimating volatility. |
| Linear Programming MT | Solves small and large scale linear programming problems. |
| Linear Regression MT | Least squares estimation. |
| Loglinear Analysis MT | Analysis of categorical data using log-linear analysis. |
| Maximum Likelihood MT | Maximum likelihood estimation of the parameters of statistical models. |
| Nonlinear Equations MT | Solves systems of nonlinear equations having as many equations as unknowns. |
| Optimization | Unconstrained optimization. |
| Time Series MT | Exact ML estimation of VARMAX, VARMA, ARIMAX, ARIMA, and ECM models subject to general constraints on the parameters. Panel data estimation. Cointegration and unit root tests. |
See also
References
- ^ Burschka, Martin A.; Ehud Kalpan; Keith Purpura; Clay Reid; Ellen Bush (April 14, 1987). “The Scientific PC: Software for Problem Solving”. PC Magazine. Vol. 6, no. 7. Ziff-Davis. pp. 155–178 – via Google Books.
- ^ Ernst, Steve (April 20, 2001). “Aptech Systems thrives on Gauss-powered growth”. Puget Sound Business Journal. Vol. 21, no. 51. American City Business Journals. p. 6A – via Gale.
- ^ Anderson, Richard G. (April–June 1992). “The Guass Programming System: A Review”. Journal of Applied Econometrics. 7 (2). Wiley: 215–219. JSTOR 2285031.
- ^ Perkel, Jeffrey M. (June 20, 2005). “Biology by the Numbers”. The Scientist. Vol. 19, no. 12. pp. 32–33. ProQuest 200012247.
- ^ Sodhi, Manmohan S.; Wayne Holland (October 2003). “GAUSS Mathematical and Statistical System 5.0”. OR/MS Today. Vol. 30, no. 5. Institute for Operations Research and the Management Sciences. pp. 46 et seq. – via Gale.
- ^ “Explore GAUSS Application Modules | Aptech”. store.aptech.com. Retrieved 2022-03-29.