Monte carlo methods for confidence interval estimation using the bootstrap technique

Stephen T. Buckland

doi:10.1080/02664768300000017

Monte carlo methods for confidence interval estimation using the bootstrap technique

Stephen T. Buckland^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

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 language	English
Pages (from-to)	194-212
Number of pages	19
Journal	Journal of Applied Statistics
Volume	10
Issue number	2
DOIs	https://doi.org/10.1080/02664768300000017
Publication status	Published - 1 Jan 1983

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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.",

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Monte carlo methods for confidence interval estimation using the bootstrap technique

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