Abstract Details
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Activity Number:
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396
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Type:
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Invited
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Date/Time:
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Tuesday, August 6, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and the Environment
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| Abstract - #307371 |
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Title:
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Matrix-Free Computations for Gaussian Markov Random Fields and Related Spatial Processes on Regular Lattice
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Author(s):
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Debashis Mondal*+
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Companies:
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The University of Chicago
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Keywords:
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conditional simulations ;
de Wijs process ;
discrete cosine transformation ;
Lanczos algorithm ;
REML ;
trace estimation
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Abstract:
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Since their introduction in statistics through the seminal work of Julian Besag, Gaussian Markov random fields and related spatial processes on regular lattice have been successfully applied to account for discrete spatial variation in both point-referenced and areal-unit data. Applications include astronomy, agriculture, computer vision, climate studies, epidemiology, image analysis, geology and other areas of environmental science. In recent years, new perspectives have emerged in connecting Gaussian Markov random fields with geostatistical models, and in advancing vast statistical computations. In this talk, I will focus on various novel matrix free computations for spatial processes on regular lattice. I will provide applications for both areal-unit and point-referenced data. Part of this talk is based on joint work with Somak Dutta.
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Authors who are presenting talks have a * after their name.
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