EMPIRICAL LIKELIHOOD AND GENERAL ESTIMATING EQUATIONS

• 成果类型: Article
• 署名作者: QIN, J; LAWLESS, J
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176325370
• 发表日期: 1994
• 页码: 300-325
• 关键词: quasi-likelihood; INFORMATION; models

摘要

For some time, so-called empirical likelihoods have been used heuristically for purposes of nonparametric estimation. Owen showed that empirical likelihood ratio statistics for various parameters theta(F) of an unknown distribution F have limiting chi-square distributions and may be used to obtain tests or confidence intervals in a way that is completely analogous to that used with parameteric likelihoods. Our objective in this paper is twofold: first, to link estimating functions or equations and empirical likelihood; second, to develop methods of combining information about parameters. We do this by assuming that information about F and theta is available in the form of unbiased estimating functions. Empirical likelihoods for parameters are developed and shown to have properties similar to those for parameteric likelihood. Efficiency results for estimates of both theta and F are obtained. The methods are illustrated on several problems, and areas for future investigation are noted.