Monte carlo methods for confidence interval estimation using the bootstrap technique

Stephen T. Buckland*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

An extension of Monte Carlo methods to confidence interval estimation, using the bootstrap technique, is investigated. The approach may have considerable potential for parameters that have estimators with complicated analytic properties but with probability distributions that can be simulated. Potential fields of application include ratio estimation, compound distributions and estimation of probabilities.

Original languageEnglish
Pages (from-to)194-212
Number of pages19
JournalJournal of Applied Statistics
Volume10
Issue number2
DOIs
Publication statusPublished - 1 Jan 1983

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