The workshop introduces a group of emanating academics and established professionals, who are engaged in spatial analysis, demography, epidemiology, ecology or econometrics, to the novel methodology of spatial filtering. Non-parametric spatial filtering and semi-parametric spatial filtering belong to a developing family of techniques that is geared toward analyzing geo-referenced data in an exploratory and confirmatory framework. The dissemination of this newer methodology via the summer workshop is important for several reasons: [1] the conceptional simplicity of spatial filtering makes spatial statistics more accessible to a very wide user group, one that is familiar with conventional statistics but not necessarily with spatial statistics; [2] the increasing appearance of spatial filtering approaches in methodological and applied literatures from a broad disciplinary scope indexes both its growing popularity and a need for more researchers to be trained in its uses; [3] spatial filtering dramatically simplifies the implementation of linear, nonlinear, generalized linear as well as mixed models for spatially autocorrelated data; [4] in order to evaluate and critique the spatial filtering approaches, the workshop will juxtapose them with established modes of analyzing spatial data; and, finally, [5] the workshop participants will be introduced to software tools that prototype spatial filtering algorithms within the widely available R computing-platform. The workshop is designed to allow participants to practice their acquired skills on a wide range of provided or personally owned geo-referenced datasets.

Depending on their specific backgrounds, the participants will be trained during the workshop to become well-versed users, informed instructors, or potential developers of the emerging spatial filtering methodology. With the rapidly increasing volume of geo-referenced data and the constitution of geographic information systems to support virtually every facet of our daily lives, skills to analyze geo-referenced data in an informed manner are becoming increasingly relevant. This workshop contributes toward providing academic and professional specialist these analytical skills. Potential participants will follow a formal application procedure in order to obtain one of the limited 25 seats of this one-week summer workshop in 2008. A selection committee will ensure the pluralism and qualifications of the selected group of participants in such a way that a diverse mix of scholars will attend the workshop.

Agency
National Science Foundation (NSF)
Institute
Division of Social and Economic Sciences (SES)
Type
Standard Grant (Standard)
Application #
0724964
Program Officer
Cheryl L. Eavey
Project Start
Project End
Budget Start
2007-09-01
Budget End
2009-02-28
Support Year
Fiscal Year
2007
Total Cost
$66,794
Indirect Cost
Name
University of Texas at Dallas
Department
Type
DUNS #
City
Richardson
State
TX
Country
United States
Zip Code
75080