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NeurIPS 2005

A Bayesian Spatial Scan Statistic

Conference Paper Artificial Intelligence · Machine Learning

Abstract

We propose a new Bayesian method for spatial cluster detection, the “Bayesian spatial scan statistic, ” and compare this method to the standard (frequentist) scan statistic approach. We demonstrate that the Bayesian statistic has several advantages over the frequentist approach, including increased power to detect clusters and (since randomization testing is unnecessary) much faster runtime. We evaluate the Bayesian and fre- quentist methods on the task of prospective disease surveillance: detect- ing spatial clusters of disease cases resulting from emerging disease out- breaks. We demonstrate that our Bayesian methods are successful in rapidly detecting outbreaks while keeping number of false positives low.

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Context

Venue
Annual Conference on Neural Information Processing Systems
Archive span
1987-2025
Indexed papers
30776
Paper id
105593347703068727