Please note that some information may be outdated!


A Statistical Environment Based
on the XLISP Language

Xlisp-Stat is an extensible statistical computing environment for data analysis, statistical computing and research, with an emphasis on providing a framework for exploring the use of dynamic graphical methods. It was written and designed by Luke Tierney and described in the book Tierney L. (1990), LISP-STAT: An Object-Oriented Environment for Statistical Computing and Dynamic Graphics, NewYork, NY: Wiley. You can get all the current information about Xlisp-Stat from the Xlisp-Stat homepage.

Some useful links related to Xlisp-Stat:
Arc is a free, menu-driven, statistical analysis tool for regression problems based on Xlisp-Stat, as described in the book by Cook R.D. and  Weisberg S. (1999), Applied Regression Including Computing and Graphics, New York, Wiley.
Arc allows to applies graphical methods to regression problems, as well as fitting linear model, generalized linear model, nonlinear models, and methods for Regression Graphics (see the book by Cook R.D. (1998), Regression Graphics: Ideas for Studying Regressions through Graphics, New York, Wiley).
UCLA Xlisp-Stat Archive
Main archive of contributed code from lisp-stat users.
ViSta, the Visual Statistics System, features statistical visualizations that are highly dynamic and very interactive.
Other links about Lisp:
XLISP-PLUS: Another Object-oriented Lisp   On-line manual  

Steele G.L. (1990) Common Lisp the Language On-line book.


Addition to Arc

The following items link to some of the code written in Xlisp-Stat I wrote during the last years. Most of the files are add-ons to Arc (you may want to see also Arc Add-Ons in the Arc Web page), but some may be of more general use. Please feel free to use and report any problem at
Overdisperse Poisson (March 21, 2000)
The document poisson-extra-var.pdf describes how to use Arc to fit overdisperse Poisson data. Get the necessary code in poisson-extra-var.lsp. The data file salmonellaTA98.lsp  is used as an example in this document.
Improved Help dialog (Feb 2001)
This add-on provides an improved help facility for Arc. Get the documentation in helpdlg.pdf, and the the code in helpdlg.lsp.
The available help may be shown on the listener or on a separate window, but in the latter case you need the additional file displayw.lsp.
Display text window (Feb 2000)
Creates a window for displaying text. Extends the Mac-only display window (Tierney, p. 360) to work on all platforms. Thanks to Forrest Young who provides the main code from VISTA.
Download the file displayw.lsp and type (help 'display-window) and (help 'collect-output) to read the documentation.
Shapiro-Wilk test of normality (April 1999)
Calculates the Shapiro and Wilk's W statistic and its significance level.
The file as181.lsp contains the lisp translation from the Fortran algorithm AS 181, Applied Statistics, 1982.
To see the documentation for the main function type (help 'shapiro-wilk-w).
In Arc when the *wilk-shapiro-test* variable is T the test is automatically reported on the summary obtained from the histogram pop-up menu and in the normal probability plot.
Royston, J. P. (1982), An extension of Shapiro and Wilk's W test for normality to large samples, Applied Statistics, 31, 115-124
Royston, J. P. (1982), [Algorithm AS 181] The W test for normality, Applied Statistics, 31, 76-180
Uncorrelated 2D views (July 2000)
The file uncorr-2d.lsp provides the lisp code for the graphical method reviewed in the article A Review and Computer Code for Assessing the Structural Dimension of a Regression Model: Uncorrelated 2D Views (2001). Computational Statistics & Data Analysis, Vol. 36(2), pp. 163-177.
The dataset for the example discussed in the article is provided with the standard distribution of Arc in the file haystack.lsp.
Statistical Quality Control Charts (Jan 2001)
This library provides code for getting statistical quality control charts in Xlisp-Stat using Arc. Get the zipped file  and read the file qcc-readme.txt for instructions on how to install it.
SM library in XlispStat (Feb 2001)
This library provides code for nonparametric kernel density estimation and nonparametric regression in Xlisp-Stat using Arc. It is the lisp translation of the sm library for S-Plus described by Bowman and Azzalini (1997). Documentation is available in the file
Get the zipped file . In Windows OS you may use Winzip to extract the files, while in Unix/Linux you need to type
> unzip -a
for inflating the archive. In Macintosh OS you may use Stuffit Expander.
To install read the file sm-readme.txt.
Bowman, A.W. and Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford.