CrossRef Text and Data Mining
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Spatial modeling of cutaneous leishmaniasis in Iranian army units during 2014-2017 using a hierarchical Bayesian method and the spatial scan statistic
Erfan Ayubi, Mohammad Barati, Arasb Dabbagh Moghaddam, Ali Reza Khoshdel
Epidemiol Health. 2018;40:e2018032  Published online July 13, 2018

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A Bayesian spatial scan statistic for zero-inflated count data
Spatial Statistics. 2017;20:57-75   Crossref logo
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A distribution-free spatial scan statistic for marked point processes
Spatial Statistics. 2014;10:117-125   Crossref logo
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Spatio-temporal analysis of cutaneous leishmaniasis using geographic information system among Iranian Army Units and its comparison with the general population of Iran during 2005–2014
Journal of Parasitic Diseases. 2017;41(4):1114-1122   Crossref logo
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A multivariate Gaussian scan statistic forspatial data
Spatial Statistics. 2017;21:66-74   Crossref logo
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A multivariate nonparametric scan statistic for spatial data
Spatial Statistics. 2019;29:1-14   Crossref logo
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Analysis of runoff extremes using spatial hierarchical Bayesian modeling
Water Resources Research. 2013;49(10):6656-6670   Crossref logo
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Spatial Scan Statistic
Encyclopedia of Social Network Analysis and Mining. 2018;2882-2882   Crossref logo

Evaluation of image registration spatial accuracy using a Bayesian hierarchical model
Biometrics. 2014;70(2):366-377   Crossref logo
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The Study on Modified Spatial Scan Statistic
Early Warning for Infectious Disease Outbreak. 2017;329-342   Crossref logo
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Measuring the spatial accuracy of the spatial scan statistic
Spatial and Spatio-temporal Epidemiology. 2011;2(2):69-78   Crossref logo
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