NDLI: An Item Response Theory approach to spatial cluster estimation and visualization

Content Provider	Springer Nature Link
Author	Cançado, André L. F. Gomes, Antonio E. da Silva, Cibele Q. Oliveira, Fernando L. P. Duczmal, Luiz H.
Copyright Year	2016
Abstract	The scan statistic is widely used in spatial cluster detection applications of inhomogeneous Poisson processes. The most popular variant of the spatial scan is the circular scan. However, such approach has several limitations, in particular, the circular window is not suitable to make the correct description of irregularly shaped and/or unconnected clusters. Additionally, such methodology does not incorporate the tools needed for quantifying the uncertainty in the description of the most likely cluster in the analysis. In the present work we build upon the previously proposed methodology called intensity function a more efficient and accurate way of defining the uncertainty in the identification of spatial clusters using Item Response Theory ideas. Using simulated data we show that the proposed method can correctly identify primary, secondary and irregular clusters.
Starting Page	435
Ending Page	451
Page Count	17
File Format	PDF
ISSN	13528505
Journal	Environmental and Ecological Statistics
Volume Number	23
Issue Number	3
e-ISSN	15733009
Language	English
Publisher	Springer US
Publisher Date	2016-05-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inhomogeneous Poisson process Irregularly shaped spatial clusters Item Response Theory Scan statistic Uncertainty 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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