数学物理学报(英文版) ›› 2000, Vol. 20 ›› Issue (1): 68-75.

• 论文 • 上一篇    下一篇

ON CONFIDENCE REGIONS OF SEMIPARAMETRIC NONLINEAR REGRESSION MODELS (A GEOMETRIC APPROACH)

 朱仲义, 唐年胜, 韦博成   

  1. Department of Applied Mathematics, Southeast University, Nanjing 210096, China
  • 出版日期:2000-01-07 发布日期:2000-01-07
  • 基金资助:

    The project supported by NSFC and NSFJ

ON CONFIDENCE REGIONS OF SEMIPARAMETRIC NONLINEAR REGRESSION MODELS (A GEOMETRIC APPROACH)

 ZHU Zhong-Yi, TANG Nian-Sheng, WEI Bo-Cheng   

  1. Department of Applied Mathematics, Southeast University, Nanjing 210096, China
  • Online:2000-01-07 Published:2000-01-07
  • Supported by:

    The project supported by NSFC and NSFJ

摘要:

A geometric framework is proposed for semiparametric nonlinear regression models based on the concept of least favorable curve, introduced by Severini and Wong (1992). The authors use this framework to drive three kinds of improved approximate confidence regions for the parameter and parameter subset in terms of curvatures. The results obtained by Hamilton et al. (1982), Hamilton (1986) and Wei (1994) are extended to semiparametric nonlinear regression models.

关键词: Confidence regions, curvatures, nonlinear regression models, score statistic, semiparametric models

Abstract:

A geometric framework is proposed for semiparametric nonlinear regression models based on the concept of least favorable curve, introduced by Severini and Wong (1992). The authors use this framework to drive three kinds of improved approximate confidence regions for the parameter and parameter subset in terms of curvatures. The results obtained by Hamilton et al. (1982), Hamilton (1986) and Wei (1994) are extended to semiparametric nonlinear regression models.

Key words: Confidence regions, curvatures, nonlinear regression models, score statistic, semiparametric models

中图分类号: 

  • 62F25