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On matching confidence intervals and tests for some discrete distributions: methodological and computational aspects

Authors: Klaschka, J. (Jan); Reiczigel, J.;

On matching confidence intervals and tests for some discrete distributions: methodological and computational aspects

Abstract

AbstractExact two-tailed tests and two-sided confidence intervals (CIs) for a binomial proportion or Poisson parameter by Sterne (Biometrika 41:117–129, 1954) or Blaker (Can J Stat 28(4):783–798, 2000) are successful in reducing conservatism of the Clopper–Pearson method. However, the methods suffer from an inconsistency between the tests and the corresponding CIs: In some cases, a parameter value is rejected by the test, though it lies in the CI. The problem results from non-unimodality of the test p value functions. We propose a slight modification of the tests that avoids the inconsistency, while preserving nestedness and exactness. Fast and accurate algorithms for both the test modification and calculation of confidence bounds are presented together with their theoretical background.

Keywords

Computational algorithm, Parametric tolerance and confidence regions, Sterne’s and Blaker’s exact confidence interval, binomial model, exact test, Binomial model, computational algorithm, Sterne's and Blaker's exact confidence interval, Poisson model, Computational methods for problems pertaining to statistics, Exact test

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Average
Top 10%
Green
hybrid