SpaceStat software, first released in 1991, is the international standard for spatial econometric modeling.
Until SpaceStat, there was no comprehensive software package that covered a reasonable range of techniques in spatial statistics, geostatistics and spatial econometrics. Time is an integral part of SpaceStat. All views of the data can be animated, from maps to histograms to scatter plots, and all analytics are accomplished through time. All views of the data, including animations and statistical results, can be linked together to enable data discovery and reveal new insights.
SpaceStat provides an extensive suite of spatiotemporal and statistical tools including: exploratory spatial data analysis; spatial econometric analyses; and the creation of spatial weights sets and variogram models. Use SpaceStat by itself or alongside Esri’s ArcGIS to substantially extend your GIS analysis capabilities.
Note: About importing geodatabase files into spacestat — GDB versions 10.2 and later
The current version of SpaceStat imports ArcGIS GDB files version 10.1 and earlier. Users of newer versions of ArcGIS should save their geodatabase in GDB version 10.1 by adopting the following strategy on the Esri website.
SPACESTAT 4.0: Summary
SpaceStat 4.0 represents a major reworking of the underlying architecture of the application. Multithreading has been introduced improving the performance of many methods. A LeSage-Pace estimator for spatial-error and spatial-lag analyses has been added to the spatial regression method. We have designed feature enhancements in SpaceStat 4.0 that improve the appearance, functionality and performance of maps and graphs. You will also find that the extensive help documentation has been updated, revised and expanded.
SPACESTAT 3.8: Maintenance Release
This maintenance release fixes several bugs including an issue in the mixed-model regression terms dialog, and adds support for automatic checking for updates.
SUMMARY OF FEATURES IN SPACESTAT 3.6: Jacquez’ Q and Flexera licensing
With our latest release, we’ve included support for our new Q-statistic, appropriately named Jacquez’ Q. Q-statistics were developed for evaluating space-time clustering in residential histories of case-control data (Jacquez et al., 2005, 2006). Representing residential histories as space-time threads (those locations where people lived throughout the study period) instead of spatial point distributions (a disconnected set of points in space time) is one of the unique features of Jacquez’ Q.
Additionally, we’ve integrated Flexera’s software licensing capabilities to support our network licensed and individually licensed product installations. See our online help for more details.
SUMMARY OF FEATURES IN SPACESTAT 3.5: Geostatistical Discretization and Deconvolution
In release 3.5, we included support for additional options in kriging (discretization and deconvolution), allowing you to perform kriging from one geography to another. We also introduced a new graph type, the 2D histogram, which lets you explore how objects are distributed with respect to two variables. See online help for more details.
SUMMARY OF FEATURES IN SPACESTAT 3: Geodatabase Integration
In this important update, SpaceStat extended the range of import/export file types to the geodatabase (gdb) format. SpaceStat’s advanced visualization, space-time analysis, and modeling techniques are easily integrated into workflows that use Esri technologies. For example, you can use Esri’s ArcGIS to acquire, edit, and manipulate your data, and then use SpaceStat to analyze time-dynamic data; to target health interventions, to assess health disparities, and to undertake predictive modeling.
(Note on terminology change: Based on the results of usability studies and a survey we conducted, in this release, we have changed the method name “spatial interpolation” to “scale conversion/interpolation” to help our users understand the multiple applications this procedure can serve for our users.)
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SUMMARY OF FEATURES IN SPACESTAT 2
In the SpaceStat version 2 release cycle, we combined the existing methods you are accustomed to (including the main types of spatial regression and spatial exploration methods) with the power and sophistication of a new data visualization interface and the ability to time-reference data. Here’s the summary of improvements:
- Geostatistical methods (simple and ordinary kriging, universal kriging, kriging with multiple external drift data sets, and Poisson kriging)
- Multi-level regression (with linear, logistic and Poisson options*
- Extensive variogram model dialog
- Poisson Smoothing
- Spatial and temporal interpolation
- Performance improvements to the statistical methods
- Export CSV files
*Additional Note on Multi-Level Regression: SpaceStat’s multi-level regression (or mixed model regression) is an extension of aspatial regression that allows the model’s regression coefficients to vary across geographical boundaries. As in aspatial regression, the main output consists of the regression coefficients (but now including details of their geographical variation). Residual datasets are listed in the data view for the user to analyze spatial patterns using the extensive suite of geospatial methods provided in SpaceStat. The regression analysis is carried out for each time interval in which the data change allowing one to visualize the progress of the regression results and spatial patterns through time. The types of multi-level regression that can be carried out in SpaceStat are linear, logistic and Poisson regression, together with the option of including dispersion for both logistic and Poisson regression.
(SpaceStat replaces our legacy Space-Time Intelligence System (STIS) product and offers all of the STIS functionality plus many added features and improvements. Additionally, SpaceStat is backwards compatible and able to open your STIS projects.)
SpaceStat is protected by U.S. patents 6,360,184, 6,460,011, 6,704,686, and 6,738,728.
All our products require Microsoft Windows™ operating systems.