go to Trig home page   Guide to GAUSS Programming - a basic introduction


 
Summary

This guide is intended to give an introduction to GAUSS which will enable the reader to produce workable programs. All the most basic and useful functions have been considered. Most areas of GAUSS have been covered to some degree. Some aspects of good programming technique have been touched on.

Throughout the guide, the emphasis has been on getting to a stage where useful programs could be written. However, there is much in GAUSS that has been left out. As mentioned earlier, there are a great deal of standard functions in GAUSS which have not been touched upon. Mostly these have been of a mathematical sort, although a large number of those left out are to do with matrix manipulation. The hope is that the reader will now be sufficiently confident in his understanding of the language to explore further the possibilities of GAUSS.

It was stated that the intention of the course is to instil familiarity with GAUSS. If we have been successful, then the reader need have no fear of sailing to GAUSS's wilder shores. In addition to the "basic" GAUSS, there are a number of "add-on" libraries and routines. These are nothing more than advanced GAUSS routines, and the user will soon discover that these are more straightforward than they appear at first glance.

There are some warnings. GAUSS is much more a nuts-and-bolts operation than other econometric packages, and it demands a higher level of competence than these others. Moreover, GAUSS itself is not perfect. The authors have experienced a number of idiosyncracies, "unexplained" features, and just plain errors. Testing should be an integral part of the development of any GAUSS program. GAUSS programming needs, and should be given, a large degree of caution.

Of course, if GAUSS is only used in the form of the "add-ons", then this is a minor issue. However, the big advantage of learning the language is that the user is no longer restricted to whatever is on display. A standard application would almost certainly be better handled elsewhere - and more trustworthily. It is in the non-standard that GAUSS excels. We have written programs to create and analyse cross-product matrices, produce cohort studies, run Monte Carlo simulations, and calculate and analyse observation patterns for participants in a panel survey. Of these models, only the simulation and cohort datasets could reasonably have been run under other packages. Of the others, the cross-product analysis cannot be achieved elsewhere because of the nature of the dataset; and the observation histories is an interpretation of the data peculiar to us.

In short, GAUSS is hard work but very flexible. Even if the user does not care to write his own programs because he uses the standard applications, there may come a point at which he may wish to modify these to suit some end of his own. Hopefully, this coursebook has provided the tools to do so.

1 Add-on packages

Because the standard GAUSS suite is a relatively low-level matrix manipulation language, a large number of parties now provide what are termed "add-ons". These are prewritten procedures enabling fairly complex operations to be carried out with a basic knowledge of GAUSS and a minimum of fuss.

For example, current add-ons include packages for
  • OLS regression
  • constrained and non-linear estimation
  • financial and technical analysis
  • simulation
  • data analysis
  • forecasting
Some of these are written by Aptech, and some by third parties. Most of these need to be purchased. and they come with the documentation to allow them to be used effectively. On the whole. For a current list of Aptech and accredited third-party packages, visit the products section of the Aptech site.

In addition, there is a large amount of code on the web for free use. Good starting points are the Aptech site, the GAUSS Source Code Archive at American University and GAUSS at CodEc. Finally, try the gaussians mailing list for comments and help on code.

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