LAD estimation for nonlinear regression models with randomly censored data. (English) Zbl 1092.62067
Summary: The least absolute deviations (LAD) estimation for nonlinear regression models with randomly censored data is studied and the asymptotic properties of LAD estimators such as consistency, boundedness in probability and asymptotic normality are established. Simulation results show that for the problems with censored data, LAD estimation performs much more robustly than the least squares estimation.
MSC:
62J02 | General nonlinear regression |
62N02 | Estimation in survival analysis and censored data |
62F12 | Asymptotic properties of parametric estimators |
62N01 | Censored data models |