GAUSS (software)

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GAUSS
Developer(s) Aptech Systems
Initial release 1984
Stable release 14 / 2013-10-24
Operating system Linux, OS X, Windows
Type programming language
License proprietary
Website www.aptech.com

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. It was first published in 1984 for MS-DOS and is currently also available for Linux, Mac OS X and Windows.

Examples of Functions Included in Run-Time Library[edit]

  • GAUSS has several Application Modules as well as functions in its Run-Time Library (i.e., functions that come with GAUSS without extra cost)
    • Qprog — Quadratic programming
    • SqpSolvemt - Sequential quadratic programming
    • QNewton - Quasi-Newton unconstrained optimization
    • EQsolve - Nonlinear equations solver

GAUSS Applications[edit]

A range of toolboxes are available for GAUSS at additional cost. See http://www.aptech.com/products/gauss-applications/ for complete listing of products.

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 loglinear 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. Unit root and cointegration tests.

See also[edit]

External links[edit]