Estimation in the mean residual life regression model. (English) Zbl 0803.62083
Summary: The proportional mean residual life model was originally proposed by D. Oakes and T. Dasu [Biometrika 77, No. 2, 409-410 (1990; Zbl 0713.62018)]. 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.
MSC:
62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
62E20 | Asymptotic distribution theory in statistics |