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Activity Number:
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137
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2008 : 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 - #302558 |
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Title:
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Mapping Spatial Aggregation from Counts Data: A Penalized Likelihood Approach
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Author(s):
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Nels Grevstad*+
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Companies:
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Metropolitan State College of Denver
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Address:
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Dept of Mathematics, denver, CO, 80217-3362,
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Keywords:
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counts ; aggregation ; spatial statistics ; penalized likelihood ; smoothing spline
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Abstract:
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A model for counts data on a spatial domain is presented. The counts are assumed to follow the negative binomial distribution, with both the mean and dispersion parameter allowed to vary spatially. The ratio of the mean to the dispersion parameter is estimated via nonparametric penalized likelihood regression. The dispersion parameter is assumed to follow a parametric model whose parameters are estimated via minimization of a variant of the the generalized approximate cross validation score of Xiang and Wahba (1996) proposed by Gu and Xiang (2001), which is simultaneously used to estimate the smoothing parameter associated with estimation of the mean to dispersion parameter ratio. The increased flexibility of the model permitted by allowing the dispersion parameter to vary spatially is illustrated through spatial maps of certain indices of aggregation using real and simulated data.
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