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Abstract Details
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Activity Number:
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456
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 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 - #305971 |
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Title:
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Bayesian Factor Analysis with Spatial Factor Loadings
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Author(s):
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Eleanor Neeley*+ and William Christensen and Stephan Sain
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Companies:
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Brigham Young University and Brigham Young University and Geophysical Statistics Project
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Address:
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223 TMCB, Provo, UT, 84602, United States
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Keywords:
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Factor Analysis ;
Spatial Modeling ;
NARCCAP ;
Climate Models
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Abstract:
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In this paper we present a Bayesian spatial factor analysis that introduces spatial structure on the factor loadings through an intrinsic CAR prior. We discuss the identifiably and computation issues of the model. The model is applied as a method for combining output from the regional climate models of the North American Regional Climate Change Assessment Program (NARCCAP), both current and future climate projections. The spatial factor loadings are necessary so that the factor model can identify geographical locations of discrepancies among the regional climate models. The spatial factor analysis model provides an interpretable approach to combining climate model output that helps account for the high correlation among climate model projections.
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