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Abstract Details

Activity Number: 303
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics and the Environment
Abstract - #305932
Title: Informative Estimation and Selection of Time-Varying Correlation Structure for Spatial Data
Author(s): Xueying Zheng*+ and Annie Qu
Companies: The University of Hong Kong and University of Illinois at Urbana-Champaign
Address: 1329 N Lincoln St, Champaign, IL, 61801, United States
Keywords: correlation structure ; oracle property ; quadratic inference function ; spatial data
Abstract:

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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