NDLI: A spatial scan statistic for zero-inflated Poisson process

Content Provider	Springer Nature Link
Author	Cançado, André L. F. da Silva, Cibele Q. Silva, Michel F.
Copyright Year	2014
Abstract	The scan statistic is widely used in spatial cluster detection applications of inhomogeneous Poisson processes. However, real data may present substantial departure from the underlying Poisson process. One of the possible departures has to do with zero excess. Some studies point out that when applied to data with excess zeros, the spatial scan statistic may produce biased inferences. In this work, we develop a closed-form scan statistic for cluster detection of spatial zero-inflated count data. We apply our methodology to simulated and real data. Our simulations revealed that the Scan-Poisson statistic steadily deteriorates as the number of zeros increases, producing biased inferences. On the other hand, our proposed Scan-ZIP and Scan-ZIP+EM statistics are, most of the time, either superior or comparable to the Scan-Poisson statistic.
Starting Page	627
Ending Page	650
Page Count	24
File Format	PDF
ISSN	13528505
Journal	Environmental and Ecological Statistics
Volume Number	21
Issue Number	4
e-ISSN	15733009
Language	English
Publisher	Springer US
Publisher Date	2014-03-11
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inhomogeneous Poisson process Scan statistic Spatial clusters Zero-inflation Ecology Statistics Mathematical and Computational Biology Evolutionary Biology
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Environmental Science Statistics, Probability and Uncertainty

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