数学物理学报(英文版) ›› 2000, Vol. 20 ›› Issue (3): 471-475.

• 论文 • 上一篇    

CONSERVATIVE ESTIMATING FUNCTIONIN THE NONLINEAR REGRESSION MODEL WITHAGGREGATED DATA

 林路   

  1. Department of Mathematics, Nankai University, Tianjin 300071, China
  • 收稿日期:1999-04-27 修回日期:1999-04-08 出版日期:2000-05-20 发布日期:2000-05-20
  • 基金资助:

    Supported by the National Natural Sciences Foundation and the National Education
    Committee Doctoral Foundation.

CONSERVATIVE ESTIMATING FUNCTIONIN THE NONLINEAR REGRESSION MODEL WITHAGGREGATED DATA

 LIN Lu   

  1. Department of Mathematics, Nankai University, Tianjin 300071, China
  • Received:1999-04-27 Revised:1999-04-08 Online:2000-05-20 Published:2000-05-20
  • Supported by:

    This research is supported by NNSF project 19771049 of China

摘要:

The purpose of this paper is to study the theory of conservative estimating
functions in nonlinear regression model with aggregated data. In this model, a quasi-score
function with aggregated data is defined. When this function happens to be conservative, it
is projection of the true score function onto a class of estimation functions. By constructing,
the potential function for the projected score with aggregated data is obtained, which have
some properties of log-likelihood function.

关键词: Nonlinear regression model with aggregated data, quasi-score function, con-
servative vector field,
potential function

Abstract:

The purpose of this paper is to study the theory of conservative estimating
functions in nonlinear regression model with aggregated data. In this model, a quasi-score
function with aggregated data is defined. When this function happens to be conservative, it
is projection of the true score function onto a class of estimation functions. By constructing,
the potential function for the projected score with aggregated data is obtained, which have
some properties of log-likelihood function.

Key words: Nonlinear regression model with aggregated data, quasi-score function, con-
servative vector field,
potential function

中图分类号: 

  • 62A10