A Kernel-Based Spectral Model for Non-Gaussian Spatio-Temporal Processes

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A Kernel-Based Spectral Model for Non-Gaussian Spatio-Temporal Processes

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/9074

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dc.contributor.author Wikle, Christopher K., 1963-
dc.contributor.other University of Missouri-Columbia. College of Arts and Sciences. Department of Statistics
dc.date.accessioned 2010-11-17T18:38:23Z
dc.date.available 2010-11-17T18:38:23Z
dc.date.issued 2002
dc.identifier.citation Statistical Modelling, 2, pp. 299-314. en_US
dc.identifier.uri http://hdl.handle.net/10355/9074
dc.description This is the pre-print version of the article found in Statistical Modelling (http://smj.sagepub.com/). en_US
dc.description.abstract Spatio-temporal processes can often be written as hierarchical state-space processes. In situations with complicated dynamics such as wave propagation, it is difficult to parameterize state transition functions for high-dimensional state processes. Although in some cases prior understanding of the physical process can be used to formulate models for the state transition, this is not always possible. Alternatively, for processes where one considers discrete time and continuous space, complicated dynamics can be modeled by stochastic integro-difference equations in which the associated redistribution kernel is allowed to vary with space and/or time. By considering a spectral implementation of such models, one can formulate a spatio-temporal model with relatively few parameters that can accommodate complicated dynamics. This approach can be developed in a hierarchical framework for non-Gaussian processes, as demonstrated on cloud intensity data. en_US
dc.description.sponsorship This research was made possible by a grant from the U.S. Environmental Protection Agency's Science to Achieve Results (STAR) program, Assistance Agreement No. R827257-01-0.
dc.language.iso en_US en_US
dc.publisher Statistical Modelling en_US
dc.relation.ispartof Statistics publications (MU)
dc.subject Bayesian en_US
dc.subject dynamic models en_US
dc.subject dilation en_US
dc.subject.lcsh Statistics -- Models
dc.subject.lcsh Bayesian statistical decision theory
dc.title A Kernel-Based Spectral Model for Non-Gaussian Spatio-Temporal Processes en_US
dc.type Preprint en_US


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