Bayesian Estimating Equation Based on Hilbert Space

摘要：

This paper introduces and investigates the validity of Bayesian estimating equation derived from the Hilbert space method. A validity for Hilbert-based Bayesian estimating function is established via the Hilbert-based unbiasedness and information unbiasedness. As an application, the newly proposed method is used to construct an estimating equation for nonlinear regression model. Furthermore, the new notion is employed to lay a theoretical foundation for the penalty-based methods such as penalized likelihood and penalized least squares.

关键词： Bayesian inference Hilbert space method estimating equation valid inference penalized likelihood penalized squares.

作者: Lu LIN

作者单位: School of Mathematics and System Sciences, Shandong University,Jinan, Shandong Province, 250100, P. R. China

会议类型: 国际会议

会议名称: 2006 International Conference on Design of Experiments and Its Applications(2006实验设计及其应用国际会议)

会议地点: 天津

会议语种:英文

在线出版日期: 2006-07-09（万方平台首次上网日期，不代表论文的发表时间）