Quantifying uncertainty in the estimation of probability distributions

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2008, 5(4): 647-667. doi: 10.3934/mbe.2008.5.647

Quantifying uncertainty in the estimation of probability distributions

1.	Center for Research in Scientific Computation, North Carolina State University, Raleigh, North Carolina 27695-8205, United States

Received December 2007 Revised March 2008 Published October 2008

Abstract
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We consider ordinary least squares parameter estimation problems where the unknown parameters to be estimated are probability distributions. A computational framework for quantification of uncertainty (e.g., standard errors) associated with the estimated parameters is given and sample numerical findings are presented.

Keywords: parameter estimation, asymptotic standard error theory, confidence bands, probability distributions, approximation, size-structured populations.

Mathematics Subject Classification: 35L60,62E20,62F25,62G15,65M32,92D25.

Citation: H.T. Banks, Jimena L. Davis. Quantifying uncertainty in the estimation of probability distributions. Mathematical Biosciences & Engineering, 2008, 5 (4) : 647-667. doi: 10.3934/mbe.2008.5.647

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