GISST: Geographic Information System Statistical Toolset
In a variety of domains, ranging from military planning and intelligence to public health, analysts wish to draw inferences from spatio-temporal data. These data are often inconsistent and incomplete, suffering from both missing values and measurement error. While statistical methods are available to address these problems, existing software to implement the techniques are not easily integrated with common GIS software. Accordingly, we propose to develop the Geographic Information System Statistical Toolset (GISST). GISST will combine state-of-the-art statistical methods for handling missing data with a web-based platform to facilitate spatial and temporal analysis. Through the use of interactive filters and guided wizards, analysts will be able to import data, choose appropriate statistical algorithms, visualize the results along both spatial and temporal dimensions, and optionally output the analysis in flexible formats to share with other researchers or to integrate with other tools. The statistical methods contained within GISST are specifically designed for time-series cross-sectional data, thereby allowing researchers to glean the most information possible from their data. Integrating these methods with GIS capabilities in one common toolset will dramatically reduce the burden on analysts, which in turn will improve the quality of results.
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Quantitative Social Scien
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