Evaluation of the Gini Coefficient in Spatial Scan Statistics for Detecting Irregularly Shaped Clusters
نویسندگان
چکیده
منابع مشابه
Evaluation of the Gini Coefficient in Spatial Scan Statistics for Detecting Irregularly Shaped Clusters
Spatial scan statistics with circular or elliptic scanning windows are commonly used for cluster detection in various applications, such as the identification of geographical disease clusters from epidemiological data. It has been pointed out that the method may have difficulty in correctly identifying non-compact, arbitrarily shaped clusters. In this paper, we evaluated the Gini coefficient fo...
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Spatial scan statistics are commonly used for geographic disease cluster detection and evaluation. We propose and implement a modified version of the simulated annealing spatial scan statistic that incorporates the concept of “non-compactness” in order to penalize clusters that are very irregular in shape. We evaluate its power for the simulated annealing scan and compare it with the circular a...
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Introduction Kulldorff’s spatial scan statistic1 detects significant spatial clusters of disease by maximizing a likelihood ratio statistic over circular spatial regions. The fast localized subset scan2 enables scalable detection of proximity-constrained subsets and increases power to detect irregularly-shaped clusters, However, unconstrained subset scanning within each circular neighborhood2, ...
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Detecting significant overdensity or underdensity clusters in spatio-temporal data is critical for many real-world applications. Most existing approaches are designed to deal with regularly shaped clusters such as circular, elliptic and rectangular ones, but cannot work well on irregularly shaped clusters. In this paper, we propose GridScan, a grid-based approach for detecting irregularly shape...
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BACKGROUND The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown...
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ژورنال
عنوان ژورنال: PLOS ONE
سال: 2017
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0170736