Efficient Robbins-Monro procedure for binary data

• 成果类型: Article
• 署名作者: Joseph, VR
• 署名单位: University System of Georgia; Georgia Institute of Technology
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/91.2.461
• 发表日期: 2004
• 页码: 461470
• 关键词: sequential designs; stochastic-approximation; quantal response; CURVES

摘要

The Robbins-Monro procedure does not perform well in the estimation of extreme quantiles, because the procedure is implemented using asymptotic results, which are not suitable for binary data. Here we propose a modification of the Robbins-Monro procedure and derive the optimal procedure for binary data under some reasonable approximations. The improvement obtained by using the optimal procedure for the estimation of extreme quantiles is substantial.