A Simulation Study for the Confidence Intervals of p by Using Average Coverage Probability

  • Kim, Daehak (Department of Statistical Information, Cathodlic University of Daegu) ;
  • Jeong, Hyeong-Chul (Department of Computational Science and Statistics, Pyoungtaek University)
  • Published : 2000.12.01

Abstract

In this paper, various methods for finding confidence intervals for p of binomial parameter are reviewed. Also we introduce tow bootstrap confidence intervals for p. We compare the performance of bootstrap methods with other methods in terms of average coverage probability by Monte Carlo simulation. Advantages of these bootstrap methods are discussed.

References

  1. The American Statistician v.52 Approximate is better than "Exact" for interval estimation of binomial proportions Agresti, A.;Coull, B.A.
  2. Journal of American Statistical Association v.81 Approximate binomial confidence limits Blyth, C.R.
  3. Journal of American Statistical Association v.78 Binomial confidence intervals Blyth, C.R.;Still, H.A.
  4. Journal of American Statistical Association v.85 the accuracy of approximate intervals for a binomial parameter Chen, H.
  5. Biometrika v.26 The use of confidence or fiducial limits illustrated in the case of the binomial Clopper, C.J.;Pearson, E.S.
  6. The annals of Statistics v.7 Bootstrap methods : another look at the jackknife Efron, B.
  7. Journal of American Statistical Association v.74 A comparison of some approximate confidence intervals for the binomial parameter Ghosh, B.K.
  8. Statistical Theory with Engineering Applications Hald, A.
  9. The American Statistician v.80 A comparison of approximate interval estimators for the bernoulli parameter Leemis, L.M.;Trivedi, K.S.
  10. The Annals of Statistics v.9 On the asymptotic accuracy of Efron's bootstrap Singh, K.
  11. Statistics in Medicine v.12 Confidence intervals for a binomial proportion Vollset, S.E.
  12. Statistics Probability Letters v.7 Singh's theorem in the lattice case Woodroofe, M.;Jhun, M.
  13. Journal of American Statistical Association v.22 Probable inference, the law of succession, and statistical inference Wilson, E.B.