Title of article :
Exact computation of minimum sample size for estimation of binomial parameters
Author/Authors :
Chen، نويسنده , , Xinjia، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
Pages :
11
From page :
2622
To page :
2632
Abstract :
It is indicated by some researchers in the literature that it might be difficult to exactly determine the minimum sample size for the estimation of a binomial parameter with prescribed margin of error and confidence level. In this paper, we investigate such a very old but also extremely important problem and demonstrate that the difficulty for obtaining the exact solution is not insurmountable. Unlike the classical approximate sample size method based on the central limit theorem, we develop a new approach for computing the minimum sample size that does not require any approximation. Moreover, our approach overcomes the conservatism of existing rigorous sample size methods derived from Bernoulliʹs theorem or Chernoff–Hoeffding bound. mputational machinery consists of two essential ingredients. First, we prove that the minimum of coverage probability with respect to a binomial parameter bounded in an interval is attained at a discrete set of finite many values of the binomial parameter. This allows for reducing infinite many evaluations of coverage probability to finite many evaluations. Second, a recursive bounding technique is developed to further improve the efficiency of computation.
Keywords :
Parameter estimation , Statistical inference , Sample size , Binomial proportion
Journal title :
Journal of Statistical Planning and Inference
Serial Year :
2011
Journal title :
Journal of Statistical Planning and Inference
Record number :
2221488
Link To Document :
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