Skip to main content

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

Buy Article:

$43.00 plus tax (Refund Policy)

A double-bootstrap confidence interval must usually be approximated by a Monte Carlo simulation, consisting of two nested levels of bootstrap sampling. We provide an analysis of the coverage accuracy of the interval which takes account of both the inherent bootstrap and Monte Carlo errors. The analysis shows that, by a suitable choice of the number of resamples drawn at the inner level of bootstrap sampling, we can reduce the order of coverage error. We consider also the effects of performing a finite Monte Carlo simulation on the mean length and variability of length of two-sided intervals. An adaptive procedure is presented for the choice of the number of inner level resamples. The effectiveness of the procedure is illustrated through a small simulation study.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Bootstrap; Coverage error; Double bootstrap; Monte Carlo approximation; Percentile method; Resample; Sampling error; Stimulation

Document Type: Original Article

Affiliations: 1: University of Hong Kong, Hong Kong, 2: University of Cambridge, UK

Publication date: 1999-04-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more