Abstract Details
Activity Number:
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6
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Type:
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Invited
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Date/Time:
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Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract #314549
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View Presentation
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Title:
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Multi-Resolution Spatial Methods for Large Data Sets
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Author(s):
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Doug Nychka* and Dorit Hammerling and Zachary Thomas and William Kleiber
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Companies:
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National Center for Atmospheric Research and National Center for Atmospheric Research and The Ohio State University and University of Colorado
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Keywords:
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Spatial process ;
Splines ;
geostatistics ;
climate
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Abstract:
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Spatial data is ubiquitous in the geosciences and a basic problem is to reconstruct surfaces from irregular observations or measurements over space and time and to quantify the uncertainty in these predicted surfaces. Standard statistical methods break when applied to large data sets and so alternative approaches are needed that balance changes to the statistical models for increases in computational efficiency. A useful method (LatticeKrig) expands the field in a set of compact basis functions and places a Gaussian Markov random field (GMRF) latent model on the basis coefficients. The impact is that evaluating the model likelihood and computing spatial predictions is feasible even for tens of thousands of spatial observations on a single computational core (e.g. a laptop). In this talk two extensions of this model are presented for multivariate spatial responses and for observations on the sphere. In both cases the GMRF can be modified to account for these kinds of data without having to make substantial changes to the computational algorithms implemented in the LatticeKrig package.
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Authors who are presenting talks have a * after their name.
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