Engineering Analysis in GAUSS

Main Applications of GAUSS in Engineering

GAUSS software provides a complete set of tools for optimization, modeling, and simulation. Whether you're just getting started with data collection or finalizing results, GAUSS provides the tools you need.

Whatever your area of research, GAUSS supports all your data analysis needs, large or small.

FieldExample applications
Transportation Engineering
  • Event count models
  • Commuting choice models
  • Activity based models
  • Demand management and forecasting
  • Mode choice models
  • Free flow speed estimation
Mathematical Modeling
  • Linear and nonlinear regression models
  • Classification
  • Clustering
  • Static and dynamic systems
Simulation and Modeling
  • Markov Chain Monte Carlo simulation methods
  • State-space models
  • Kalman Filtering
  • Markov-Switching models

Optimization and other Main Functions of GAUSS for Engineering Analysis

GAUSS is able to quickly handle real world engineering analysis with the capability to analyze millions of data points, as well as solve, optimize and simulate multi-equation systems.

Data cleaning, processing, and management


  • Flexible optimization tools work with user-specified objective functions.
  • Wide selection of descent algorithms including:
    • Broyden, Fletcher, Goldfarb, and Powell (BFGS)
    • Davidon, Fletcher, and Powell (DFP)
    • Steepest descent
  • Adaptable line search methods:
    • STEPBT
    • Brent's method
    • HALF
    • Strong Wolfe's conditions
  • Specify analytical gradients or have GAUSS compute numerical gradients using the forward, central or backwards difference method.
  • Check user-supplied analytical gradients using numerical gradients.
  • Specify analytical Hessian or have GAUSS compute a numerical Hessian using the forward, central, or backwards difference method.
  • Control convergence criteria with maximum number of iterations, maximum elapsed time, maximum random search attempts, and convergence tolerance.
  • Customize optimization problems with:
    • Easy-to-specify parameter bounds.
    • Specify fixed and free parameters.
    • Dynamic algorithm switching improves convergence efficiency.
  • Specify nonlinear and linear inequality and equality constraints.

Nonlinear Systems of Equations

  • Solve user-specified equation systems of equations using a quasi-Newton algorithm with Broyden's secant update method.
  • Optional line-search algorithm or trust region (hookstep) approach for globalization.
  • Analytic or numeric derivatives options.

Discrete Choice Analysis

GAUSS provides a full suite of tools for analyzing qualitative choice models. GAUSS's discrete choice tools cover everything from binary and multinomial models to logistic regression.

  • Multinomial logit models
  • Logistic regression modeling
    • L2 and L1 regularized classifiers
    • L2 and L1-loss linear support vector machines (SVM)
  • Model selection and assessment tools
    • Full model and restricted model log-likelihoods
    • Chi-square statistics
    • Agresti’s G-squared statistic
    • McFadden’s pseudo-R-squared statistic
    • Madella’s pseudo-R-squared statistic
    • Akaike information criterion (AIC)
    • Bayesian information criterion (BIC)
    • Likelihood ratio statistics and accompanying probability values
    • Cragg and Uhler’s normed likelihood ratios
    • Count and adjusted count R-squared

GAUSS Applications Designed for Engineering


Optimization MT

Optimization MT provides tools for efficient optimization including:
  • Select descent algorithms.
  • Step-length methods.
  • Algorithm switching.

Constrained Optimization MT

Solves the nonlinear programming problem, subject to general constraints on the parameters. Includes:
  • Linear or nonlinear constraints.
  • Equality or inequality constraints.
  • Uses sequential quadratic programming method in combination with several descent methods.
  • Trust region method.

Algorithmic Derivatives

Provides tools for computing algorithmic derivatives.
  • Works independently of other applications.
  • Can be used with any application that needs derivatives.
  • The use of algorithmic derivatives can improve accuracy and convergence speeds.


CurveFit allow you to fit specified functions to data using least squares methodology.

Nonlinear Equation MT

The Nonlinear Equations MT applications module (NLSYS) solves systems of nonlinear equations where there are as many equations as unknowns.
  • Allows for user specified or numerically computed Jacobians.
  • Solves systems using the quasi-Newton algorithm with Broyden's secant updated method.
  • Can choose either a line search algorithm or a hookstep method.

Discrete Choice

Provides an adaptable, efficient, and user-friendly environment for linear data classification including
  • Binary and count models.
  • Multinomial logit models.
  • Logistic regression.
  • Tools for model selection and assessment.

Industries that use GAUSS Data Analysis Tools

Data analysts across a wide range of industries use GAUSS. GAUSS is found in

  • Universities
  • Government agencies
  • Non-governmental organizations
  • Nonprofit research organizations
  • Corporations

Whether performing stress simulations, transportation modeling, or optimizations, GAUSS offers the tools you need to succeed.

Icons of some organizations where GAUSS is used.

Benefits of GAUSS for Engineering Analysis

GAUSS provides a fast and flexible environment for engineering analysis. Whether you are solving everyday linear equations or performing cutting-edge simulations, GAUSS provides tangible advantages including:

  • Flexible, efficient, and trusted optimization routines.
  • Over 1000 pre-built statistical and mathematical functions.
  • Light-weight and efficient analytics engine designed to make the most of your hardware and provide optimized computation speed.
  • Intuitive matrix-based programming language for transparent and easy to understand programming.
  • Fully interactive environment for speeding up your workflow from exploring data to analyzing results.
  • Comprehensive documentation and examples.
  • Comprehensive data support including CSV, Excel HDF5, SAS, Stata, text delimited files.
  • Relational database support including MySQL, PostgreSQL, SQLite, Microsoft SQL Server, Oracle, IBM DB2, HBase, Hive and MongoDB.

Compatibility of GAUSS with Other Software

GAUSS is built to seamlessly integrate into any analytics environment:

  • GAUSS is fully compatible with SAS, STATA, HDF5, CSV, and Excel datasets.
  • Efficiently connect powerful analytics to any internal or customer-facing data source, application, or interface with the GAUSS Engine.
  • Full technical support for assistance when migrating from and integrating with other software platforms.

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