JSM 2004 - Toronto

Abstract #300027

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Activity Number: 366
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract - #300027
Title: Gaussian Difference Boundaries: Boundary Detection Using Distribution Theory
Author(s): Geoffrey M. Jacquez*+
Companies: BioMedware, Inc.
Address: 516 North State, Ann Arbor, MI, 48104-1236,
Keywords: boundary analysis ; neutral models
Abstract:

Geographic boundary analysis is used to detect zones of rapid change in spatially distributed variables. A wide variety of methods have been proposed and applied, including "wombling", approaches based on fuzzy set theory, and those suited for univariate as well as multivariate frameworks, and operating on real, integer and categorical data. Many of these approaches are distribution-free, relying on randomization to construct empirical distributions for evaluating the extent of "boundariness" in a given dataset. This presentation considers two salient problems in boundary analysis. First, the need for techniques based on distribution theory that are computationally fast and based on realistic assumptions. And second, the construction of neutral null models suited for the assessment of probabilities under more realistic assumptions than complete spatial randomness.

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Revised March 2004