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Abstract Details
Activity Number:
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303
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics and the Environment
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Abstract - #305932 |
Title:
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Informative Estimation and Selection of Time-Varying Correlation Structure for Spatial Data
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Author(s):
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Xueying Zheng*+ and Annie Qu
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Companies:
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The University of Hong Kong and University of Illinois at Urbana-Champaign
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Address:
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1329 N Lincoln St, Champaign, IL, 61801, United States
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Keywords:
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correlation structure ;
oracle property ;
quadratic inference function ;
spatial data
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Abstract:
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In spatial data analysis, we approximate the empirical estimator of the timer-varying correlation matrix by groups of basis matrices that represent substructures. We adopt an objective function that includes a penalty to penalize models with too many basis matrices. The proposed estimation and selection of correlation structure is able to identify more complex time-varying structures in spatial data analysis, which will increase the efficiency of the regression parameter estimator. Furthermore, the method is applicable for discrete spatial data since no specification of the likelihood function is required. Simulation studies and a real data example will confirm the effective estimation on time-varying correlation structure.
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Authors who are presenting talks have a * after their name.
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