An item response theory approach to spatial cluster estimation and visualization.
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Date
2016
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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.
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Keywords
Inhomogeneous poisson process, Item response theory, Irregularly shaped spatial clusters, Scan statistic
Citation
CANÇADO, A. L. F. et al. An item response theory approach to spatial cluster estimation and visualization. Environmental and Ecological Statistics, v. 23, p. 1-17, 2016. Disponível em: <https://link.springer.com/article/10.1007/s10651-016-0347-x>. Acesso em: 16 jan. 2018.