xldlas—A Program for Statistics
There are currently plans afoot to add a number of features to xldlas. Regressions using Probit and Logit models are high on the to-do list. A set of statistical filters is also likely to be available before long, making it possible to easily detrend data, remove outliers, and so on. HTML format log files will soon be supported. Another important task is to expand the documentation in the source code so it can be more easily modified by people other than the original author.
Like almost all freely distributable software, xldlas development is driven by user feedback. If there are features you want to see, send me some e-mail, preferably with a reference to the algorithm you would like to see implemented.
The best way to get a copy of xldlas is from its homepage at www.a42.com/~thor/xldlas. If you only have FTP access to the Internet, you can get it from ftp://sunsite.unc.edu/ (in pub/Linux/X11/xapps/math/). Both full source and a Linux ELF executable are included in the distribution, which is named xldlas-X.Y-srcbin.tgz, where X.Y is the version number (0.40 at the time of writing).
To run the included executable or compile from the source code, you'll need to have the XForms library installed on your system. For more information about XForms, visit the XForms homepage at bragg.phys.uwm.edu/xforms. Although designed to run under Linux, xldlas will apparently compile under almost all flavours of Unix for which the Xforms library exists, although a little tinkering with the Makefile is sometimes necessary. Make sure you look at the README file included in every distribution to get the latest news on compiling and running xldlas.
gnuplot is available at sunsite.unc.edu/pub/Linux/apps/math/gplotbin.tgz. It is also included in most Linux distributions.
For full functionality, xldlas also requires you to have a fairly complete TeX package installed on your machine. NTeX and teTeX are commonly used under Linux, and are available at http://sunsite.unc.edu/pub/Linux/apps/tex/.
Thor Sigvaldason has completed most of a PhD on the use of connectionist AI techniques in economic modeling. By the time this article appears, he'll either be a visiting pre-doc at the Santa Fe Institute or working in New York City. He can be reached by e-mail at firstname.lastname@example.org.
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