This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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317
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Type:
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Invited
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Date/Time:
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Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Statistical and Applied Mathematical Sciences Institute
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Abstract - #305967 |
Title:
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The Spatial Random Effects Model and Its Role in Spatial and Spatio-Temporal Statistics
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Author(s):
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Noel A. Cressie*+
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Companies:
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The Ohio State University
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Address:
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Department of Statistics, Columbus, OH, 43210-1247,
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Keywords:
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Fixed Rank Kriging ;
Fixed Rank Filtering ;
STRE model ;
VAR process ;
remote sensing
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Abstract:
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The spatial random effects (SRE) model specifies that small-scale spatial variation has a smooth component that is an inner product of known spatial basis functions (fixed in number) and random coefficients. Importantly, the coefficients are generally correlated, and their fixed-rank covariance matrix has to be inferred, along with the hidden spatial process. There is also a non-smooth, fine-scale variation component that is analogous to the nugget effect in geostatistics. When time is included, an evolutionary component can be incorporated into the SRE model, resulting in a spatio-temporal random effects (STRE) model. These models allow fast optimal prediction (kriging, filtering, smoothing, forecasting) of the hidden process; we illustrate their effectiveness on a large remote-sensing dataset.
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Authors who are presenting talks have a * after their name.
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