This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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520
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Type:
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Contributed
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Date/Time:
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Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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| Abstract - #306583 |
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Title:
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Spatio-Temporal Modeling of Sudden Infant Death Syndrome Data
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Author(s):
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Lili Zhuang*+ and Noel A. Cressie
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Companies:
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The Ohio State University and The Ohio State University
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Address:
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1958 Neil Avenue, columbus, OH, 43210,
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Keywords:
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spatio-temporal model ;
dynamical Markov random field ;
SIDS
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Abstract:
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Sudden infant death syndrome (SIDS) is a classification of death in healthy infants under one year old. However, its etiology is still largely a mystery. In this research, we analyze a spatio-temporal data set that contains yearly SIDS information from 1979 to 1984 for the counties of North Carolina. Cressie and Chan (1989) used a purely spatial model to analyze the aggregated version of this data set. In this paper, we present a spatio-temporal model from which optimal smoothing of SIDS rates can be derived. The model is hierarchical with a hidden dynamical Markov random field.
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Authors who are presenting talks have a * after their name.
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