Approximate Confidence Interval for the Mean of Poisson Distribution
Author(s) -
Manad Khamkong
Publication year - 2012
Publication title -
open journal of statistics
Language(s) - English
Resource type - Journals
eISSN - 2161-7198
pISSN - 2161-718X
DOI - 10.4236/ojs.2012.22024
Subject(s) - confidence interval , mathematics , poisson distribution , statistics , coverage probability , cdf based nonparametric confidence interval , binomial proportion confidence interval , sample size determination , interval (graph theory) , robust confidence intervals , wald test , distribution (mathematics) , sample (material) , mathematical analysis , statistical hypothesis testing , combinatorics , negative binomial distribution , chemistry , chromatography
A Poisson distribution is well used as a standard model for analyzing count data. Most of the usual constructing confidence intervals are based on an asymptotic approximation to the distribution of the sample mean by using the Wald interval. That is, the Wald interval has poor performance in terms of coverage probabilities and average widths interval for small means and small to moderate sample sizes. In this paper, an approximate confidence interval for a Poisson mean is proposed and is based on an empirically determined the tail probabilities. Simulation results show that the pro- posed interval outperforms the others when small means and small to moderate sample sizes
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