The GAUSS Mathematical and Statistical System is a fast matrix programming language widely used by scientists, engineers, statisticians, biometricians, econometricians, and financial analysts.

Designed for computationally intensive tasks, the GAUSS system is ideally suited for the researcher who does not have the time required to develop programs in C or FORTRAN but finds that most statistical or mathematical "packages" are not flexible or powerful enough to perform complicated analysis or to work on large problems.

Whatever mathematical tool or language you are now using, you'll find that GAUSS can greatly increase your productivity!

Comprehensive Environment for Modeling and Analysis
GAUSS is a complete analysis environment suitable for performing quick calculations, complex analysis of millions of data points, or anything in between. Whether you are new to computerized analysis or a seasoned programmer, the GAUSS family of products combine to offer you an easy to learn environment that is powerful and versatile enough for virtually any numerical task. Since its introduction in 1984, GAUSS has been a standard for serious number crunching and complex modeling of large-scale data.

Worldwide acceptance and use in government, industry and the academic community is a firm testament to its power and versatility. The GAUSS System can be described several ways: It is an exceptionally efficient number cruncher, a comprehensive programming language, and an interactive analysis environment. GAUSS may be the only numerical tool you will ever need.

Interactive and Fast
For simple problems GAUSS provides a fully interactive environment for exploring data, creating scenarios and analyzing results. For more complex tasks, you can write programs and save them to disk. GAUSS is exceptionally fast, providing performance comparable to compiled C or FORTRAN programs. And unlike other math packages, GAUSS's speed is equally impressive when working with problems of very large scale.

Straightforward and Efficient
While many GAUSS users never find a need to program extensively, for those who do, GAUSS provides a natural and logical environment that is easy to learn and powerful to use. At the core of GAUSS is an efficient programming language adequate for doing even the most sophisticated analysis. The basic unit ofanalysis in GAUSS is a matrix, resulting in a syntax closely resembling common mathematical expressions. Since matrix operations are assumed, most of the looping required by other languages is eliminated.

The Data Translation Loop allows transformations on variables in a data set by directly using the variable names in expressions. This streamlines data transformations and makes for shorter, more readable programs. GAUSS's Source Level Debugger greatly simplifies program development. With all of the features you would expect in a dedicated debugging system, you can quickly identify and solve program logic errors at run time.

Additionally, GAUSS handles complex numbers automatically and seamlessly. You don't have to keep track of the real and imaginary parts of a matrix. Complex numbers are handled automatically, that greatly simplifies programming for engineering and other tasks that require working with complex numbers.

The Language
As a complete programming language, the GAUSS system is both flexible and powerful. Immediately available to the GAUSS user is a wide variety of statistical, mathematical and matrix handling routines.

GAUSS can be used either interactively for short one-off commands or by creating large programs consisting of several files and libraries of functions, or anything in between.

Visualization and Presentation
GAUSS's high resolution Publication Quality Graphics gives you powerful ways to visually analyze your data and present your findings. A wide choice of graphing options are available to you, including 2D, 3D, surface, contour, polar and log graphs, as well as bar graphs, histograms, box graphs and more. Graphs can be placed in individual overlapping or tiled windows on a single page. You can export graphics files in a number of popular formats, including WMF, HP-GL/2, PostScript and EPS formats, for use in page layout and presentation packages, and GAUSS includes support for a wide range of output devices, including most of the latest printers and plotters.

The Tools You Need
GAUSS has over 400 mathematical functions built in, including LINPACK, EISPACK and BLAS routines, factorizations, decompositions, eigenvalues, distributions and equation solving functions, to provide you with all the tools you need to solve your most difficult problems. You can easily customize or add to the GAUSS function library, and optional modules provide access to many other specialized capabilities.

The GAUSS Run-Time Module (GRTM) allows users to distribute GAUSS applications that they have written to people who do not have GAUSS. Developers distribute a compiled file to end users along with the GRTM. This is available with GAUSS at no extra charge.

Other important features include: data import/export compatibility with many popular spreadsheets and databases, long period random number generators, built-in functions for efficiently handling sparse data, and a Foreign Language Interface for incorporating your favorite compiled C and FORTRAN programs directly into GAUSS programs.

With GAUSS 9.0, you have the tools that you need in order to harness the power and speed of multi-core, multi-processor, and hyper-threaded systems! GAUSS 9.0 introduces new functions for multi-threading your programs.

Another important addition is increased array support in more intrinsics and operators. This allows you to seamlessly use arrays in more of the operators and intrinsic functions.

The new threading functions enable you to define independent sections of your program that will run at the same time. These threads share the same workspace and can access all of the same symbols, procedures and keywords. You can create as many threads as you want, allowing you to take advantage of as many processors as you have.

Features and Enhancements:

• New threading functions:
  1. ThreadStat
  2. ThreadBegin
  3. ThreadEnd
  4. ThreadJoin
• Additional support for string arrays

By making use of threads in your code, you can take better advantage of the available processors on your machine. Dividing your code into multiple threads that run simultaneously can reduce the overall processing time of your programs.

Below is an illustration that shows one thread set with four threads, two that are blocks of code set off by ThreadBegin and ThreadEnd, two that are single lines of code using ThreadStat. Each thread processes at the same time as the other threads. Your program waits at the ThreadJoin command for all threads to finish. When the threads have completed, your program continues, making use of the work the threads have done.

In the example above, this block of code could potentially run nearly four times faster on a quad core machine because the threads are running simultaneously.

Threads can be created virtually anywhere--in the main code, in procedures, and in keywords. You can also create threads within other threads. This means you can multi-thread nearly anything you want and call it from anywhere in your program. You can multi-thread some or all of the procedures and keywords in your libraries and call them freely anywhere in your multi-threaded programs.

Platforms

Now available for Windows (32-bit), Linux (32-bit and 64-bit), and Sun SPARC (64-bit). Additional platforms to come include Mac OS X (32-bit and 64-bit), HP UX 11, and Windows (64-bit).

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GAUSS Data Tool is a stand-alone program for working with GAUSS data sets. GAUSS Data Tool loads the columns of the data sets into a workspace as vectors where they can be transformed or modified using simple intuitive statements. Data sets can also be created by simulation using a variety of models, e.g., probit, logit, GARCH, linear. A new version of a data set can be generated where missing data are replaced by single or multiple imputations from a maximum likelihood estimation using the EM algorithm.

Variables can be copied from one data set to another. Data sets can be merged on the basis of a keylist; i.e., one or more columns that uniquely define the observations. They can be concatenated, sorted, or added to. Variables can be dropped or kept, or modified in complex ways using any of the GAUSS operators or functions, including its powerful matrix operations.

GAUSS Data Tool is customizable by adding your own functions for modifying data. Hooks are described in the manual for adding your own procedures for simulating data or handling missing data. For the Windows version, a graphical user interface provides much of this capability in menus, toolbars, and dialogues, as well as a command line interface that turns data handling into a set of simple direct statements that make short work of complex data problems.

Newly Added Features

• ASCII and Excel file conversions

Features

• Handle missing data
• Create and simulate data sets
• Create new variables
• Delete observations
• Drop variables
• Keep variables and drop all others
• Execute GAUSS commands unfiltered
• List data sets
• List variable names and types
• Merge data sets on a key variable
• Select observations
• Sort data set
• Compute statistics on data set
• Simulate using various models, e.g., probit, logit, GARCH, linear
• Impute missing data using EM algorithm

Gaussx incorporates a full-featured set of professional state-of-the-art econometric routines that run under GAUSS. These tools can be used within Gaussx, both in research and in teaching. Alternatively, since the GAUSS source is included, individual econometric routines can be extracted and integrated in stand-alone GAUSS programs.

Gaussx provides an environment that makes econometric programming a joy. For example,
ols y c x1 x2;
does ordinary least squares, while
mcmc z1 c z3 z4;
userproc = &g_tobit;
does a Bayesian estimation of a Tobit model using Markov Chain Monte Carlo.

Gaussx provides for linear and non-linear optimization with and without parameter constraints. A full set of econometric models, estimation routines and tests are supported, including: automatic differentiation, multivariate binomial probit, VARMA process, time series analysis, LDV models, GARCH models, exponential smoothing, X12 seasonal adjustment, non-parametric analysis, neural networks, wavelets, forecasting, Kalman filter, stochastic volatility, robust estimation, Bayesian estimation, cluster analysis, financial tools, econometric tests, Monte Carlo simulation and statistical distributions.

Gaussx is designed for econometricians and financial analysts and has been continuously upgraded over 15 years. The open source paradigm allows econometricians to use GaussX routines as templates for their own code.

Gaussx is available for Windows, Linux and Unix versions of GAUSS.

New Features in Gaussx 9.0

• PANEL
• 64-bit support
• Normality tests - AD, SW, SF, PPC
• Additional survival models
• Cox Snell and martingale residuals
• Nonparametric survival estimation - SURVIVAL
• Cox proportional hazards model
• Utility functions - PERMS, COMBS, INTERP2
• Enhanced print option
• Random number generation for any distribution - RNDGEN
• Utility functions - Inverse hyperbolic functions
• Transforms vector to a normal variate - NORMAL
• Invert a function - INVERT
• Tests of distributions - PIT (Probability Integral Transformation)

Platforms:

Windows, Mac OS X, LINUX, UNIX (requires GAUSS for Windows 4.0 or higher)

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Available for Windows, Unix, and Linux

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