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Abstract Details
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Activity Number:
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184
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Type:
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Contributed
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Date/Time:
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Monday, August 1, 2011 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #301931 |
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Title:
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On Some Properties of Generalized Linear Mixed Models for Spatial Count Data
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Author(s):
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Victor De Oliveira *+
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Companies:
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The University of Texas at San Antonio
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Address:
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One UTSA Circle, San Antonio, TX, 78249 ,
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Keywords:
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Geostatistics ;
Second-order properties ;
Spatial prediction
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Abstract:
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Spatial count data occur often in many of the earth sciences, but unlike spatial continuous data, few models are available in the literature for their analysis. Currently, the most commonly used model seems to be the spatial generalized linear mixed model, which is difficult to fit. Perhaps due to the latter, most of the recent literature has concentrated on computational methods to fit this model, and some of its basic model properties are not well understood. In this talk I explore some properties and limitations of this class of models, and illustrate the findings with simulated and real datasets.
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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