Weighted jackknife-after-bootstrap: A heuristic approach

Jin Wang, J. Sunil Rao, Jun Shao

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


We investigate the problem of deriving precision estimates for bootstrap quantities. The one major stipulation is that no further bootstrapping will be allowed. In 1992, Efron derived the method of jackknife-after-bootstrap (JAB) and showed how this problem can potentially be solved. However, the applicability of JAB was questioned in situations where the number of bootstrap samples was not large. The JAB estimates were inflated and performed poorly. We provide a simple correction to the JAB method using a weighted form where the weights are derived from the original bootstrap samples. Our Monte Carlo experiments show that the weighted jackknife-after-bootstrap (WJAB) performs very well.

Original languageEnglish (US)
Pages (from-to)240-245
Number of pages6
JournalWinter Simulation Conference Proceedings
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 Winter Simulation Conference - Atlanta, GA, USA
Duration: Dec 7 1997Dec 10 1997

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety
  • Applied Mathematics


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