Document Detail

Implicit Estimation of Ecological Model Parameters.
MedLine Citation:
PMID:  23292361     Owner:  NLM     Status:  Publisher    
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.
Brad Weir; Robert N Miller; Yvette H Spitz
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-5
Journal Detail:
Title:  Bulletin of mathematical biology     Volume:  -     ISSN:  1522-9602     ISO Abbreviation:  Bull. Math. Biol.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-7     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401404     Medline TA:  Bull Math Biol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, 97331, USA,
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