Weighted Jackknife-after-Bootstrap: A Heuristic Approach

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 jackknifeafter-bootstrap (WJAB) performs very well.

• Type: Conference
• Year: 1997
• Where: WSC
• Authors: Jin Wang, J. Sunil Rao, Jun Shao
• Keywords: Bootstrap Quantities, Bootstrap Samples, JAB Estimates, Modeling And Simulation, WSC 1997