A NOTE ON JORGENSENS ITERATIVELY DEFINED STATISTICS

• 成果类型: Article
• 署名作者: TSAI, CL
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• 发表日期: 1994
• 页码: 781786
• 关键词: non-linear regression; maximum-likelihood estimation; models; diagnostics; nonlinearity; CURVATURE; inference; accuracy

摘要

The Newton-Raphson and Fisher scoring iteratively reweighted least squares methods are two fundamental tools for computing parameter estimators and deletion diagnostics. Jorgensen (1993) proposed a modified method to compute deletion diagnostics. In this paper, we study the relationship between Jorgensen's, Newton-Raphson and Fisher scoring one-step deletion estimators by using the observed and expected Fisher information matrices. In addition, we extend Jorgensen's true leverage and approximate leverage from binary regression models to general model settings.