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.
|Simulation and Modeling||
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
- Easy data importation with support for SAS, STATA, Excel, CSV, HDF5, GAUSS matrices, GAUSS Datasets, and ASCII text files
- Data visualization
- Recoding and reclassification tools
- Data scaling methods including euclidean scaling, median scaling, maximum absolute value scaling, mid-range scaling, and standard deviation scaling
- Flexible handling of missing values including missing value imputation, pairwise deletion, and listwise deletion
- Dummy variable creation from categorical variables
- Data sorting and merging and both the file and matrix level
- 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:
- Brent's method
- 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 provides tools for efficient optimization including:
Constrained Optimization MT
|Solves the nonlinear programming problem, subject to general constraints on the parameters. Includes:
|Provides tools for computing algorithmic derivatives.
|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.
|Provides an adaptable, efficient, and user-friendly environment for linear data classification including
Industries that use GAUSS Data Analysis Tools
Data analysts across a wide range of industries use GAUSS. GAUSS is found in
- Government agencies
- Non-governmental organizations
- Nonprofit research organizations
Whether performing stress simulations, transportation modeling, or optimizations, GAUSS offers the tools you need to succeed.
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.