Parameter Subset Selection and Multiple Comparisons of Poisson Rate Parameters with Misclassification

We develop a fully Bayesian model for estimating a Poisson rate parameter subject to the presence of both false-positive and false-negative misclassification of the counts for a multiple sample scheme. We also propose decision-theoretic based parameter subset selection and multiple comparison methods for comparing Poisson rate parameters where counts are subject to misclassification. We apply our new data analysis methodologies to real-data examples. Probabilities used in these methods are approximated via Gibbs samplers

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Year of publication:	2018
Authors:	Stamey, James D.
Other Persons:	Bratcher, Tom L. (contributor) ; Young, Dean M. (contributor)
Publisher:	[2018]: [S.l.] : SSRN
Subject:	Schätztheorie \| Estimation theory \| Statistischer Test \| Statistical test