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A simulation study for the approximate confidence intervals of hypergeometric parameter by using actual coverage probability  

Kim, Dae-Hak (Department of mathematic, Catholic University of Daegu)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.6, 2011 , pp. 1175-1182 More about this Journal
Abstract
In this paper, properties of exact confidence interval and some approximate confidence intervals of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the approximation of hypergeometirc distribution to the binomial and normal distribution respectively. Approximate confidence intervals based on these approximation are also adequately discussed. The performance of exact confidence interval estimates and approximate confidence intervals of hypergeometric parameter is compared in terms of actual coverage probability by small sample Monte Carlo simulation.
Keywords
Actual coverage probability; binomial approximation; exact confidence interval; hyper-geometric parameter; normal approximation;
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Times Cited By KSCI : 2  (Citation Analysis)
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