Efficient bootstrap simulation

A. C. Dvison, D. V. Hinkley, E. Schechtman

Research output: Contribution to journalArticlepeer-review

172 Scopus citations

Abstract

Bootstrap methods are simulation methods for assessing sampling properties of statistical estimates. We discuss two ideas for making the simulation more efficient. The first idea is to balance the simulated samples, and the second idea is to make explicit use approximations which do not require simulation. Both ideas are illustrated with three examples.

Original languageEnglish
Pages (from-to)555-566
Number of pages12
JournalBiometrika
Volume73
Issue number3
DOIs
StatePublished - 1 Dec 1986
Externally publishedYes

Keywords

  • Balanced samples
  • Bias
  • Bootstrap
  • Correlation
  • Eigenvalue
  • Hypergeometric distribution
  • Jakknife
  • Mean
  • Normal approximation
  • Permutation

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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