ESTIMATION IN THE MEAN RESIDUAL LIFE REGRESSION-MODEL
成果类型：
Article
署名作者：
MAGULURI, G; ZHANG, CH
刊物名称：
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
ISSN/ISSBN：
1369-7412
发表日期：
1994
页码：
477-489
关键词：
摘要：
The proportional mean residual life model was originally proposed by Oakes and Dasu. This model can be extended to a regression model with explanatory variables. We consider the problem of estimation of the regression parameter in this general model. We investigate two types of estimator, of which one is based on the maximum likelihood equation of the exponential regression model, and the other is based on the underlying proportional hazards structure of the model and Cox's estimating equation. We show that these estimators are consistent and asymptotically normal. We compare their performance by simulations.