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Activity Number:
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484
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Type:
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Invited
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Date/Time:
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Thursday, August 10, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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International Indian Statistical Association
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| Abstract - #305017 |
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Title:
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Computation and Modeling for Large Space-Time Environmental Datasets
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Author(s):
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Michael L. Stein*+
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Companies:
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The University of Chicago
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Address:
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Department of Statistics, Chicago, IL, 60637,
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Keywords:
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Gaussian processes ; stratospheric ozone
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Abstract:
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Our ability to analyze large space-time environmental datasets often is constrained by computational considerations. Most environmental monitoring datasets have regular patterns in their space-time locations, such as a fixed monitoring network with evenly spaced observation times. We will consider space-time models under which exact or highly accurate approximations to the likelihood can be computed for such datasets, paying particular attention to the common situation in which there is a modest fraction of missing observations.
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