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


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Quantifying uncertainty in the estimation of probability distributions

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

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

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


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