| Implicit Estimation of Ecological Model Parameters. | |
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MedLine Citation:
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PMID: 23292361 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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We introduce an implicit method for state and parameter estimation and apply it to a stochastic ecological model. The method uses an ensemble of particles to approximate the distribution of model solutions and parameters conditioned on noisy observations of the state. For each particle, it first determines likely values based on the observations, then samples around those values. This approach has a strong theoretical foundation, applies to nonlinear models and non-Gaussian distributions, and can estimate any number of model parameters, initial conditions, and model error covariances. The method is called implicit because it updates the particles without forming a predictive distribution of forward model integrations. As a point of comparison for different assimilation techniques, we consider examples in which one or more bifurcations separate the true parameter from its initial approximation. The implicit estimator is asymptotically unbiased, has a root-mean-squared error comparable to or less than the other methods, and is accurate even with small ensemble sizes. |
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Authors:
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Brad Weir; Robert N Miller; Yvette H Spitz |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2013-1-5 |
Journal Detail:
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Title: Bulletin of mathematical biology Volume: - ISSN: 1522-9602 ISO Abbreviation: Bull. Math. Biol. Publication Date: 2013 Jan |
Date Detail:
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Created Date: 2013-1-7 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401404 Medline TA: Bull Math Biol Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, 97331, USA, bweir@ceoas.oregonstate.edu. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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