What is GAUSS?#

GAUSS is a matrix programming language designed for computationally intensive tasks in statistics, econometrics, and data analysis. Developed by Aptech Systems since 1984, it combines the speed of compiled code with the flexibility of an interpreted environment.

Who Uses GAUSS?#

GAUSS is used by:

Central banks for forecasting, policy analysis, and financial stability research
Academic economists for econometric research and teaching
Financial institutions for risk modeling and quantitative analysis
Transportation researchers for discrete choice modeling
Government agencies for economic forecasting

Why Choose GAUSS?#

Purpose-built for econometrics. Unlike general-purpose languages, GAUSS was designed from the start for matrix mathematics and statistical computing. This means:

Matrix operations are first-class citizens, not library add-ons
Statistical functions work the way econometricians expect
Time series, panel data, and limited dependent variable tools are available out of the box or through specialized add-ons

Speed. GAUSS compiles to native code and uses optimized numerical libraries. For computationally intensive work—Monte Carlo simulations, bootstrapping, large-scale optimization—this matters.

40 years of reliability. Code written in GAUSS in the 1990s still runs today. When you build research infrastructure in GAUSS, it lasts.

Interactive and batch modes. Explore data interactively in the GUI, then run production jobs in batch mode on servers.

What Can You Do with GAUSS?#

Time series analysis:

ARIMA, GARCH, VAR/VECM models
State-space models and Kalman filtering
Forecasting with multiple methods

Econometric estimation:

OLS, GLS, IV, GMM
Maximum likelihood estimation
Bayesian methods (MCMC)

Panel data:

Fixed and random effects
Dynamic panels
Clustered standard errors

Discrete choice:

Logit, probit, multinomial models
Mixed logit with simulation
Nested logit structures

General computation:

Matrix algebra and linear algebra
Numerical optimization
Simulation and Monte Carlo

Core Concepts#

Everything is a matrix. In GAUSS, scalars are 1×1 matrices, vectors are Nx1 or 1xN matrices, and multi-dimensional data lives in matrices or dataframes.

Dataframes extend matrices with column names, types (numeric, string, date, category), and metadata—similar to dataframes in R or pandas.

Procedures are user-defined functions. GAUSS ships with hundreds of built-in procedures; you can write your own or use add-on packages.

Libraries group related procedures. Load them with library libname; to access specialized functionality.

GAUSS vs. Other Tools#

Aspect	GAUSS	MATLAB	Stata/EViews
Primary focus	Econometrics	Engineering	Statistics/Econ
Matrix syntax	Native	Native	Command-based
Speed	Fast	Fast	Moderate
Custom code	Easy	Easy	Limited
Time series	Strong (TSMT)	Moderate	Strong
GUI workflow	GUI + code	GUI + code	GUI-centric

See our “Coming from…” guides for detailed comparisons:

Getting Started#

Ready to try GAUSS?

GAUSS Quickstart — Run your first GAUSS code in 10 minutes
Running Existing Code — If you have existing GAUSS code to run
The Absolute Basics for Beginners — If you’re new to programming