An optimal estimating equation based on the first three cumulants

• 成果类型: Article
• 署名作者: Li, B
• 署名单位: Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/85.1.103
• 发表日期: 1998
• 页码: 103114
• 关键词: quasi-likelihood estimation; generalized linear-models; EFFICIENCY; BIAS

摘要

For improving on quasilikelihood-estimation two types of quadratic estimating equations have been proposed, one based on the Edgeworth expansion, the other on the generalisation of the quasi-score. The first requires that the skewness of observations has a small departure from the exponential family; the second requires the knowledge of both skewness and kurtosis. We introduce an optimal quadratic estimating equation applicable when the skewness is not small and the-kurtosis is unknown;Apart from optimality, the manner in which skewness-is incorporated ensures that its misspecification does not affect root n-consistency, and that the estimator enjoys an invariance property akin to that of the bias-corrected maximum likelihood estimate. Simulations indicate a solid improvement in accuracy.