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