Mapping rates associated with polygons |
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Authors: | Noel Cressie Hal S Stern Deanne Reber Wright |
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Institution: | (1) Department of Statistics, 1958 Neil Avenue, 404 Cockins Hall, The Ohio State University, Columbus, OH 43210-1247, USA (e-mail: ncressie@stat.ohio-state.edu), US;(2) Department of Statistics, Iowa State University, Ames, IA 50011-1210, USA (e-mail: hstern@iastate.edu), US;(3) Pioneer Hi-Bred International, Inc., 7300 NW 62 Avenue, Johnston, IA 50131, USA (e-mail: wrightdean@phibred.com), US |
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Abstract: | Suppose that geographic data under investigation are rates associated with polygons. For example, disease incidence, mortality,
and census undercount data may be displayed as rates. Spatial analysis of data of this sort can be handled very naturally
through Bayesian hierarchical statistical modeling, where there is a measurement process at the first level, an explanatory
process at the second level, and a prior probability distribution on unknowns at the third level. In our paper, we shall feature
epidemiological data, specifically disease-incidence rates, and the “polygons” referred to in the title are typically states
or counties. |
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Keywords: | : Bayesian inference disease mapping hierarchical models loss functions spatio-temporal models |
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