GAUSS 24 – NOW AVAILABLE

For professionals in data-driven disciplines from finance to physics, GAUSS has long been the go-to source for specialised models, techniques and applications. However, GAUSS is also a comprehensive environment that gives you everything you need to develop, adapt, execute and generate publication quality graphics for virtually any problem or project.

GAUSS is ideal for rapid prototyping as well as complete implementation of a wide range of scientific and business models. All functions and programs can be altered by the user and easily integrated with C/C++, Java, FORTRAN and other environments.

Learn more about the specific strengths GAUSS offers these diverse industries:

Econometrics

• Efficient data organisation, management, and publication quality presentation.
• Functions are easily adaptable to fit individual model specifications, making it an ideal program for univariate, multivariate, panel series, cross-sectional and time-series analysis.
• Includes a quick and reliable maximum likelihood routine.
• Provides pre-programmed classical regression analysis tools with the framework necessary for implementing modern regression techniques including time-varying parameters, Markov-Switching models, Bayesian analysis and DSGE models.
• Computation of large datasets and complex models can be done quickly. This, combined with tools for process automation, documentation, and presentation, allow for efficient econometric analysis.
• Additional GAUSS Applications designed for Econometrics include:
  • Algorithmic Derivatives
  • Constrained Maximum Likelihood / Constrained Maximum Likelihood MT
  • Constrained Optimization / Constrained Optimization MT
  • Descriptive Statistics MT
  • Discrete Choice
  • FANPAC MT
  • Linear Regression MT
  • Maximum Likelihood / Maximum Likelihood MT
  • Optimization / Optimization MT
  • Time Series MT

Finance

The GAUSS finance procedures combined with keyword functions make the platform appropriate for easy updating of results, while simultaneously meeting the needs of specialized models. Documentation and visualization of model results is clear, thorough and easy to interpret and share.

GAUSS is capable of efficiently handling large datasets and provides tools for easy data management making it suitable for conducting analysis using high frequency, real-time data.

There is a large set of functions and applications specifically designed for finance, including:

• • Binomial Options Pricing: Pre-programmed routines for implementing binomial options pricing model to both European and American call and put options.
  • AmericanBSCall (American Black and Scholes call)
  • European BSPut
  • AnnualTradingDay
  • GetNextWeekDay

• FANPAC MT: The FANPAC MT GAUSS Application provides built in commands for complete modeling and analysis of standard finance univariate and multivariate models. FANPAC MT includes easy to use keyword commands for analyzing the complete family of ARIMA, ARCH, GARCH, and IGARCH models.
• Additional GAUSS Applications designed for Finance include:
  • Algorithmic Derivatives
  • Constrained Maximum Likelihood / Constrained Maximum Likelihood MT
  • Constrained Optimization / Constrained Optimization MT
  • Descriptive Statistics MT
  • Linear Programming MT
  • Linear Regression MT
  • Maximum Likelihood / Maximum Likelihood MT
  • Optimization / Optimization MT
  • Time Series MT

Epidemiology

GAUSS offers a complete set of tools for data organization, analysis, and presentation. Survey data, cross-sectional data, and large panel data can easily be easily managed using a number of conditional data selection and sorting tools.

GAUSS is equipped to efficiently conduct statistical inference, correlation and regression analysis as well as categorical, multivariate, time-series and survival analysis.

Applications are also available to enhance standard data analysis:

• Descriptive Statistics MT: Available application includes methods for analyzing and generating contingency tables.
• Regression Analysis: Available suites of pre-programmed discrete choice and panel series regression tools make regression analysis easy.

Engineering/Physics

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. Built-in functions and can import other programs such as C and FORTRAN.

• • GAUSS performs high efficiency modelling and simulation of complex systems of equations using structures, threading and parallel computing.
  • GAUSS provides a complete set of tools for standard and advanced applications of numerical analysis, applied linear algebra, initial and boundary value problems, Fourier analysis and optimisation.
  • Optimization MT implements wide selection of descent algorithms, step-length methods, and “on-the-fly” algorithm switching. User controlled options allow for model specificity and optimisation flexibility.
  • Additional GAUSS Applications designed for Engineering/Physics include:
    • Algorithmic Derivatives
    • Constrained Optimization / Constrained Optimization MT
    • CurveFit
    • Nonlinear Equations MT

Social Science

GAUSS’s matrix language, combined with its efficient computation methodology, makes large scale data analysis and modeling fast and easy to update.

• • • Regression analysis is made easy with an available full suite of pre-programmed discrete choice regression tools.
    • Time Series MT includes techniques for panel series modeling including fixed effects models and random effects models.
    • Additional GAUSS Applications designed for Social Sciences include:
      • Algorithmic Derivatives
      • Constrained Maximum Likelihood / Constrained Maximum Likelihood MT
      • Descriptive Statistics MT
      • Discrete Choice
      • Loglinear Analysis MT
      • Maximum Likelihood / Maximum Likelihood MT

GAUSS in Education

GAUSS provides students and researchers with the high-end analytical tools needed to solve the complex problems they’ll face in both academic and professional careers.

GAUSS: Advantages in education

• • • Fast and Efficient: GAUSS has many advantages for computational econometrics. At its core, GAUSS is a fast and efficient matrix language. The GAUSS matrix language allows for a very natural translation from the mathematical equations in a journal article or textbook to a program that you can run on your laptop, or a large cluster computer. This results in efficiency and speed in developing algorithms, customizing and implementing new code or running large data sets.
    • Interactive:  The highly interactive user interface of GAUSS provides a fully-featured environment with top of the line graphics. This makes it easy to interact with data and models and provides immediate feedback along every step of algorithm development.
    • Advanced Tools:  GAUSS includes many innovative tools to aid in the creation and understanding of your GAUSS programs and the mathematics that they represent. Examples include: Interactive graphics editing — Step through your program line-by-line while viewing the changes to your data— Automatic or manual threading for precise resource utilization in cluster, cloud and production applications — And too many others to mention. GAUSS has the tools to facilitate your work and make you more productive.
    • Intuitive:  The matrix based programming language maps directly and intuitively to logic and theory. This, combined with powerful smart editor features, makes transforming classroom theories into computations straightforward and easy to learn.
    • Customizable:   GAUSS has the flexibility to customize models to solve a broader range of problems. This provides the opportunity for Students to extend theoretical knowledge to real-world problem solving, empowering Students to work in a wide variety of positions and offer more value to future employers.
    • GAUSS Applications:  are a complete suite of in-house pre-programmed and modifiable procedures to help users quickly tackle all of their computational needs in various fields of study and industry, including Statistics, Econometrics, Machine Learning / Statistical Learning, and more.

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