ESTIMATING THE REAL PARAMETER IN A 2-SAMPLE PROPORTIONAL ODDS MODEL

• 成果类型: Article
• 署名作者: WU, CO
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176324526
• 发表日期: 1995
• 页码: 376-395
• 关键词: information; EFFICIENCY; likelihood

摘要

This paper considers efficient estimation of the Euclidean parameter theta in the proportional odds model G(1 - G)(-1) = theta F(1 - F)(-1) when two independent i.i.d. samples with distributions F and G, respectively, are observed. The Fisher information I(theta) is calculated based on the solution of a pair of integral equations which are derived from a class of more general semiparametric models. A one-step estimate is constructed using an initial root N-consistent estimate and shown to be asymptotically efficient in the sense that its asymptotic risk achieves the corresponding minimax lower bound.