Less Square Estimate Edgeworth Expansion Bootstrap Distribution Block Bootstrap Move Block Bootstrap 
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  1. Athreya, K. (1987). Bootstrap of the mean in the infinite variance case, Ann. Stat.,15(2), 724–731.MATHCrossRefMathSciNetGoogle 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.MATHCrossRefMathSciNetGoogle 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.MATHCrossRefGoogle Scholar
  8. Bose, A. and Babu, G. (1991). Accuracy of the bootstrap approximation, Prob. Theory Related Fields, 90(3), 301–316.MATHCrossRefMathSciNetGoogle 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.MATHCrossRefMathSciNetGoogle Scholar
  11. David, H.A. (1981). Order Statistics, Wiley, New York.MATHGoogle Scholar
  12. Davison, A.C. and Hinkley, D. (1997). Bootstrap Methods and Their Application, Cambridge University Press, Cambridge.MATHGoogle Scholar
  13. DiCiccio, T. and Efron, B. (1996). Bootstrap confidence intervals, with discussion, Stat. Sci., 11(3), 189–228.MATHCrossRefMathSciNetGoogle Scholar
  14. Efron, B. (1979). Bootstrap methods: another look at the Jackknife, Ann. Stat., 7(1), 1–26.MATHCrossRefMathSciNetGoogle Scholar
  15. Efron, B. (1981). Nonparametric standard errors and confidence intervals, with discussion, Can. J. Stat., 9(2), 139–172.MATHCrossRefMathSciNetGoogle Scholar
  16. Efron, B. (1987). Better bootstrap confidence intervals, with comments, J. Am. Stat. Assoc., 82(397), 171–200.MATHCrossRefMathSciNetGoogle 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.MATHGoogle Scholar
  19. Falk, M. and Kaufman, E. (1991). Coverage probabilities of bootstrap confidence intervals for quantiles, Ann. Stat., 19(1), 485–495.MATHCrossRefGoogle Scholar
  20. Freedman, D. (1981). Bootstrapping regression models, Ann. Stat., 9(6), 1218–1228.MATHCrossRefGoogle Scholar
  21. Ghosh, M., Parr, W., Singh, K., and Babu, G. (1984). A note on bootstrapping the sample median, Ann. Stat., 12, 1130–1135.MATHCrossRefMathSciNetGoogle 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.MATHCrossRefGoogle Scholar
  25. Hall, P. (1988). Rate of convergence in bootstrap approximations, Ann. Prob., 16(4), 1665–1684.MATHCrossRefGoogle Scholar
  26. Hall, P. (1989a). On efficient bootstrap simulation, Biometrika, 76(3), 613–617.MATHCrossRefGoogle Scholar
  27. Hall, P. (1989b). Unusual properties of bootstrap confidence intervals in regression problems, Prob. Theory Related Fields, 81(2), 247–273.MATHCrossRefGoogle Scholar
  28. Hall, P. (1990). Asymptotic properties of the bootstrap for heavy-tailed distributions, Ann. Prob., 18(3), 1342–1360.MATHCrossRefGoogle 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.MATHCrossRefMathSciNetGoogle 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.MATHCrossRefMathSciNetGoogle Scholar
  33. Hall, P., Horowitz, J., and Jing, B. (1995). On blocking rules for the bootstrap with dependent data, Biometrika, 82(3), 561–574.MATHCrossRefMathSciNetGoogle Scholar
  34. Helmers, R. (1991). On the Edgeworth expansion and bootstrap approximation for a studentized U-statistic, Ann. Stat., 19(1), 470–484.MATHCrossRefMathSciNetGoogle Scholar
  35. Konishi, S. (1991). Normalizing transformations and bootstrap confidence intervals, Ann. Stat., 19(4), 2209–2225.MATHCrossRefMathSciNetGoogle Scholar
  36. Künsch, H.R. (1989). The Jackknife and the bootstrap for general stationary observations, Ann. Stat., 17(3), 1217–1241.MATHCrossRefGoogle Scholar
  37. Lahiri, S.N. (1999). Theoretical comparisons of block bootstrap methods, Ann. Stat., 27(1), 386–404.MATHCrossRefMathSciNetGoogle Scholar
  38. Lahiri, S.N. (2003). Resampling Methods for Dependent Data, Springer-Verlag, New York.MATHGoogle 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.MATHCrossRefGoogle Scholar
  41. Lehmann, E.L. (1999). Elements of Large Sample Theory, Springer, New York.MATHGoogle 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.MATHCrossRefMathSciNetGoogle Scholar
  44. Politis, D., Romano, J., and Wolf, M. (1999). Subsampling, Springer, New York.MATHGoogle Scholar
  45. Politis, D. and White, A. (2004). Automatic block length selection for the dependent bootstrap, Econ. Rev., 23(1), 53–70.MATHMathSciNetCrossRefGoogle Scholar
  46. Shao, J. and Tu, D. (1995). The Jackknife and Bootstrap, Springer-Verlag, New York.MATHGoogle Scholar
  47. Silverman, B. and Young, G. (1987). The bootstrap: to smooth or not to smooth?, Biometrika, 74, 469–479.MATHCrossRefMathSciNetGoogle Scholar
  48. Singh, K. (1981). On the asymptotic accuracy of Efron’s bootstrap, Ann. Stat., 9(6), 1187–1195.MATHCrossRefGoogle Scholar
  49. Tong, Y.L. (1990). The Multivariate Normal Distribution, Springer, New York.MATHGoogle Scholar
  50. van der Vaart, A. (1998). Asymptotic Statistics, Cambridge University Press, Cambridge.MATHGoogle Scholar

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© Springer Science+Business Media, LLC 2008

Authors and Affiliations

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

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