Abstract Details
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Activity Number:
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306
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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| Abstract - #310015 |
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Title:
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Joint Modeling of Paired Spatially Correlated Multilevel Functional Data
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Author(s):
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Beth Tidemann-Miller*+ and Brian J. Reich and Ana-Maria Staicu
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Companies:
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North Carolina State University and North Carolina State University and North Carolina State University
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Keywords:
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multivariate ;
bivariate functional data ;
functional principal components ;
bivariate spatial modeling
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Abstract:
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Due to the large size of modern data sets, there is an ever-increasing need for computationally efficient inferential methods designed for realistic models of large observed functional data sets. We introduce an innovative modeling framework for the analysis of multivariate functional data, where each individual functional component exhibits multilevel and spatial structures. The proposed methodology uses a functional principal components based approach for multivariate functional data, which has important advantages in the dimensionality reduction of the data and brings considerable computational savings. The proposed procedure is illustrated through simulation studies and data from a colon carcinogenesis experimental study.
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Authors who are presenting talks have a * after their name.
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