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Keywords

Less Square Estimate Edgeworth Expansion Bootstrap Distribution Block Bootstrap Move Block Bootstrap 
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References

  1. Athreya, K. (1987). Bootstrap of the mean in the infinite variance case, Ann. Stat.,15(2), 724–731.zbMATHCrossRefMathSciNetGoogle Scholar
  2. Beran, R. (2003). The impact of the bootstrap on statistical algorithms and theory, Stat. Sci., 18(2), 175–184.CrossRefMathSciNetGoogle Scholar
  3. Bickel, P.J. (1992). Theoretical comparison of different bootstrap t confidence bounds, in Exploring the Limits of Bootstrap, R. LePage and L. Billard (eds.) John Wiley, New York, 65–76.Google Scholar
  4. Bickel, P.J. (2003). Unorthodox bootstraps, Invited paper, J. Korean Stat. Soc., 32(3), 213–224.MathSciNetGoogle Scholar
  5. Bickel, P.J. and Freedman, D. (1981). Some asymptotic theory for the bootstrap, Ann. Stat., 9(6), 1196–1217.zbMATHCrossRefMathSciNetGoogle Scholar
  6. Bickel, P.J., Göetze, F., and van Zwet, W. (1997). Resampling fewer than n observations: gains, losses, and remedies for losses, Stat. Sinica, 1, 1–31.Google Scholar
  7. Bose, A. (1988). Edgeworth correction by bootstrap in autoregressions, Ann. Stat., 16(4), 1709–1722.zbMATHCrossRefGoogle Scholar
  8. Bose, A. and Babu, G. (1991). Accuracy of the bootstrap approximation, Prob. Theory Related Fields, 90(3), 301–316.zbMATHCrossRefMathSciNetGoogle Scholar
  9. Bose, A. and Politis, D. (1992). A review of the bootstrap for dependent samples, in Stochastic Processes and Statistical Inference, B.L.S.P Rao and B.R. Bhat, (eds.), New Age, New Delhi.Google Scholar
  10. Carlstein, E. (1986). The use of subseries values for estimating the variance of a general statistic from a stationary sequence, Ann. Stat., 14(3), 1171–1179.zbMATHCrossRefMathSciNetGoogle Scholar
  11. David, H.A. (1981). Order Statistics, Wiley, New York.zbMATHGoogle Scholar
  12. Davison, A.C. and Hinkley, D. (1997). Bootstrap Methods and Their Application, Cambridge University Press, Cambridge.zbMATHGoogle Scholar
  13. DiCiccio, T. and Efron, B. (1996). Bootstrap confidence intervals, with discussion, Stat. Sci., 11(3), 189–228.zbMATHCrossRefMathSciNetGoogle Scholar
  14. Efron, B. (1979). Bootstrap methods: another look at the Jackknife, Ann. Stat., 7(1), 1–26.zbMATHCrossRefMathSciNetGoogle Scholar
  15. Efron, B. (1981). Nonparametric standard errors and confidence intervals, with discussion, Can. J. Stat., 9(2), 139–172.zbMATHCrossRefMathSciNetGoogle Scholar
  16. Efron, B. (1987). Better bootstrap confidence intervals, with comments, J. Am. Stat. Assoc., 82(397), 171–200.zbMATHCrossRefMathSciNetGoogle Scholar
  17. Efron, B. (2003). Second thoughts on the bootstrap, Stat. Sci., 18(2), 135–140.CrossRefMathSciNetGoogle Scholar
  18. Efron, B. and Tibshirani, R. (1993). An Introduction to the Bootstrap, Chapman and Hall, New York.zbMATHGoogle Scholar
  19. Falk, M. and Kaufman, E. (1991). Coverage probabilities of bootstrap confidence intervals for quantiles, Ann. Stat., 19(1), 485–495.zbMATHCrossRefGoogle Scholar
  20. Freedman, D. (1981). Bootstrapping regression models, Ann. Stat., 9(6), 1218–1228.zbMATHCrossRefGoogle Scholar
  21. Ghosh, M., Parr, W., Singh, K., and Babu, G. (1984). A note on bootstrapping the sample median, Ann. Stat., 12, 1130–1135.zbMATHCrossRefMathSciNetGoogle Scholar
  22. Gin’e, E. and Zinn, J. (1989). Necessary conditions for bootstrap of the mean, Ann. Stat., 17(2), 684–691.CrossRefMathSciNetGoogle Scholar
  23. Göetze, F. (1989). Edgeworth expansions in functional limit theorems, Ann. Prob., 17, 1602–1634.CrossRefGoogle Scholar
  24. Hall, P. (1986). On the number of bootstrap simulations required to construct a confidence interval, Ann. Stat., 14(4), 1453–1462.zbMATHCrossRefGoogle Scholar
  25. Hall, P. (1988). Rate of convergence in bootstrap approximations, Ann. Prob., 16(4), 1665–1684.zbMATHCrossRefGoogle Scholar
  26. Hall, P. (1989a). On efficient bootstrap simulation, Biometrika, 76(3), 613–617.zbMATHCrossRefGoogle Scholar
  27. Hall, P. (1989b). Unusual properties of bootstrap confidence intervals in regression problems, Prob. Theory Related Fields, 81(2), 247–273.zbMATHCrossRefGoogle Scholar
  28. Hall, P. (1990). Asymptotic properties of the bootstrap for heavy-tailed distributions, Ann. Prob., 18(3), 1342–1360.zbMATHCrossRefGoogle Scholar
  29. Hall, P. (1992). Bootstrap and Edgeworth Expansion, Springer-Verlag, New York.Google Scholar
  30. Hall, P. (2003). A short prehistory of the bootstrap, Stat. Sci., 18(2), 158–167.CrossRefGoogle Scholar
  31. Hall, P., DiCiccio, T., and Romano, J. (1989). On smoothing and the bootstrap, Ann. Stat., 17(2), 692–704.zbMATHCrossRefMathSciNetGoogle Scholar
  32. Hall, P. and Martin, M.A. (1989). A note on the accuracy of bootstrap percentile method confidence intervals for a quantile, Stat. Prob. Lett., 8(3), 197–200.zbMATHCrossRefMathSciNetGoogle Scholar
  33. Hall, P., Horowitz, J., and Jing, B. (1995). On blocking rules for the bootstrap with dependent data, Biometrika, 82(3), 561–574.zbMATHCrossRefMathSciNetGoogle Scholar
  34. Helmers, R. (1991). On the Edgeworth expansion and bootstrap approximation for a studentized U-statistic, Ann. Stat., 19(1), 470–484.zbMATHCrossRefMathSciNetGoogle Scholar
  35. Konishi, S. (1991). Normalizing transformations and bootstrap confidence intervals, Ann. Stat., 19(4), 2209–2225.zbMATHCrossRefMathSciNetGoogle Scholar
  36. Künsch, H.R. (1989). The Jackknife and the bootstrap for general stationary observations, Ann. Stat., 17(3), 1217–1241.zbMATHCrossRefGoogle Scholar
  37. Lahiri, S.N. (1999). Theoretical comparisons of block bootstrap methods, Ann. Stat., 27(1), 386–404.zbMATHCrossRefMathSciNetGoogle Scholar
  38. Lahiri, S.N. (2003). Resampling Methods for Dependent Data, Springer-Verlag, New York.zbMATHGoogle Scholar
  39. Lahiri, S.N. (2006). Bootstrap methods, a review, in Frontiers in Statistics, J. Fan and H. Koul (eds.), Imperial College Press, London, 231–256.Google Scholar
  40. Lee, S. (1999). On a class of m out of n bootstrap confidence intervals, J.R. Stat. Soc. B, 61(4), 901–911.zbMATHCrossRefGoogle Scholar
  41. Lehmann, E.L. (1999). Elements of Large Sample Theory, Springer, New York.zbMATHGoogle Scholar
  42. Loh, W. and Wu, C.F.J. (1987). Discussion of “Better bootstrap confidence intervals” by Efron, B., J. Amer. Statist. Assoc., 82, 188–190.CrossRefGoogle Scholar
  43. Politis, D. and Romano, J. (1994). The stationary bootstrap, J. Am. Stat. Assoc., 89(428), 1303–1313.zbMATHCrossRefMathSciNetGoogle Scholar
  44. Politis, D., Romano, J., and Wolf, M. (1999). Subsampling, Springer, New York.zbMATHGoogle Scholar
  45. Politis, D. and White, A. (2004). Automatic block length selection for the dependent bootstrap, Econ. Rev., 23(1), 53–70.zbMATHMathSciNetCrossRefGoogle Scholar
  46. Shao, J. and Tu, D. (1995). The Jackknife and Bootstrap, Springer-Verlag, New York.zbMATHGoogle Scholar
  47. Silverman, B. and Young, G. (1987). The bootstrap: to smooth or not to smooth?, Biometrika, 74, 469–479.zbMATHCrossRefMathSciNetGoogle Scholar
  48. Singh, K. (1981). On the asymptotic accuracy of Efron’s bootstrap, Ann. Stat., 9(6), 1187–1195.zbMATHCrossRefGoogle Scholar
  49. Tong, Y.L. (1990). The Multivariate Normal Distribution, Springer, New York.zbMATHGoogle Scholar
  50. van der Vaart, A. (1998). Asymptotic Statistics, Cambridge University Press, Cambridge.zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Anirban DasGupta
    • 1
  1. 1.Department of StatisticsPurdue UniversityWest Lafayette

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