The estimating function bootstrap

@inproceedings{Feifang1999TheEF,
  title={The estimating function bootstrap},
  author={HU Feifang and John D. Kalbfleisch},
  year={1999}
}
The authors propose a bootstrap procedure which estimates the distribution of an estimating function by resampling its terms using bootstrap techniques. Studentized versions of this so-called estimating function (EF) bootstrap yield methods which are invariant under reparametrizations. This approach often has substantial advantage, both in computation and accuracy, over more traditional bootstrap methods and it applies to a wide class of practical problems where the data are independent but not… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 49 references

Prepivoting to reduce level error of confidence

  • R. Beran
  • sets. Biometrika,
  • 1987
Highly Influential
7 Excerpts

Relevance Weighted Smoothing and a New Bootstrap

  • F. Hu
  • Unpublished doctoral dissertation, The University…
  • 1994
Highly Influential
10 Excerpts

On generalized score tests

  • D. D. Boos
  • The American Statistician, 46, 327–333.
  • 1992
Highly Influential
9 Excerpts

A review of bootstrap confidence intervals (with discussion)

  • T. J. DiCiccio, J. P. Romano
  • Journal of the Royal Statistical Society B,
  • 1988
Highly Influential
5 Excerpts

Bootstrap methods: another look at the jackknife

  • B. Efron
  • The Annals of Statistics, 7, 1–26.
  • 1979
Highly Influential
7 Excerpts

Some aspects of Edgeworth expansions in statistics and probability

  • R. N. Bhattacharya
  • New Perspectives in Theoretical and Applied…
  • 1987
Highly Influential
2 Excerpts

The effect of Monte Carlo approximation on coverage error of double bootstrap confidence intervals

  • S.M.S. Lee, G. A. Young
  • Journal of the Royal Statistical Society, Series…
  • 1999

provide a review of some of the literature and some interesting

  • Small, Yang
  • 1999
1 Excerpt

Breakdown theory for bootstrap quantiles

  • K. Singh
  • The Annals of Statistics, 26, 1719–1732.
  • 1998

Similar Papers

Loading similar papers…