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Zero-inflated models with application to spatial count data

Zero-inflated models with application to spatial count data Count data arises in many contexts. Here our concern is with spatial count data which exhibit an excessive number of zeros. Using the class of zero-inflated count models provides a flexible way to address this problem. Available covariate information suggests formulation of such modeling within a regression framework. We employ zero-inflated Poisson regression models. Spatial association is introduced through suitable random effects yielding a hierarchical model. We propose fitting this model within a Bayesian framework considering issues of posterior propriety, informative prior specification and well-behaved simulation based model fitting. Finally, we illustrate the model fitting with a data set involving counts of isopod nest burrows for 1649 pixels over a portion of the Negev desert in Israel. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental and Ecological Statistics Springer Journals

Zero-inflated models with application to spatial count data

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References (30)

Publisher
Springer Journals
Copyright
Copyright © 2002 by Kluwer Academic Publishers
Subject
Life Sciences; Ecology; Statistics, general; Mathematical and Computational Biology; Evolutionary Biology
ISSN
1352-8505
eISSN
1573-3009
DOI
10.1023/A:1020910605990
Publisher site
See Article on Publisher Site

Abstract

Count data arises in many contexts. Here our concern is with spatial count data which exhibit an excessive number of zeros. Using the class of zero-inflated count models provides a flexible way to address this problem. Available covariate information suggests formulation of such modeling within a regression framework. We employ zero-inflated Poisson regression models. Spatial association is introduced through suitable random effects yielding a hierarchical model. We propose fitting this model within a Bayesian framework considering issues of posterior propriety, informative prior specification and well-behaved simulation based model fitting. Finally, we illustrate the model fitting with a data set involving counts of isopod nest burrows for 1649 pixels over a portion of the Negev desert in Israel.

Journal

Environmental and Ecological StatisticsSpringer Journals

Published: Oct 10, 2004

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