[Openspace] Space Time Analysis of Regional Systems (STARS) is released

[Julia Koschinsky]

This posting from Serge Rey might be of interest to the list 
since several subscribers had questions about open source 
software and space-time analysis.

Julia

*******************

From: Serge Rey <serge at ROHAN.SDSU.EDU
Date: July 13, 2004 10:05:50 PM CDT
To: WRSA at LISTSERV.ARIZONA.EDU
Subject: Space Time Analysis of Regional Systems (STARS) is 
released
Reply-To: Serge Rey <serge at ROHAN.SDSU.EDU

STARS: Space Time Analysis of Regional Systems
Version 0.7.2
Released 2004-July-09

STARS is an exploratory data analysis package designed for 
variables measured on geographical units over time. It 
combines a series of statistical and mapping views together 
with some newly developed measures for space-time 
statistical analysis. The views support several types of 
dynamic visualization:

     - Linking different views to examine a given 
observation across different dimensions (spatial, temporal, 
distributional)
     - Conditioning (brushing) one or more destination views 
on the selection of a set of observations on an origin view
     - Animations of of maps, distributions, box plots, 
scatter plots, parallel coordinate plots and other views 
over time
     - Spatial traveling
     - Roaming windows
     - View generated views (creating new views from 
existing views)

STARS includes a suite of computational modules:
     - Classic descriptive statistics
     - Exploratory Spatial Data Analysis (local and global 
spatial autocorrelation in a dynamic context)
     - Inequality Analysis
     - Distributional mixing and mobility
     - Classic Markov and Spatial Markov methods

STARS also includes utility methods for creating different 
types of geographical weight matrices, time series 
covariation matrices, variable transformations, and for 
reading ArcView shapefiles to develop STARS projects.

STARS is written in Python, making heavy use of Numpy and 
Tkinter, and is open source software released under GNU 
General Public License (GPL). It is cross platform, and has 
been successfully run on Mac Os X, Linux, and most versions 
of Windows.

Source code, a Windows binary installer, as well as user 
guides, QuickTime tutorials, background papers, user-list, 
and other documentation can be found at the project's 
homepage:

 	http://stars-py.sf.net

Serge Rey	http://typhoon.sdsu.edu/rey.html