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Highest posterior mass prediction intervals for binomial and poisson distributions

K. Krishnamoorthy () and Shanshan Lv
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K. Krishnamoorthy: University of Louisiana at Lafayette
Shanshan Lv: University of Louisiana at Lafayette

Metrika: International Journal for Theoretical and Applied Statistics, 2018, vol. 81, issue 7, 775-796

Abstract: Abstract The problems of constructing prediction intervals (PIs) for the binomial and Poisson distributions are considered. New highest posterior mass (HPM) PIs based on fiducial approach are proposed. Other fiducial PIs, an exact PI and approximate PIs are reviewed and compared with the HPM-PIs. Exact coverage studies and expected widths of prediction intervals show that the new prediction intervals are less conservative than other fiducial PIs and comparable with the approximate one based on the joint sampling approach for the binomial case. For the Poisson case, the HPM-PIs are better than the other PIs in terms of coverage probabilities and precision. The methods are illustrated using some practical examples.

Keywords: Coverage probability; Fiducial method; Highest probability mass function; Precision; Predicting distribution (search for similar items in EconPapers)
Date: 2018
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