| Abstract: | Summary This research develops a semiparametric kernel‐based estimator of hazard functions which does not assume proportional hazards. The maintained assumption is that the hazard functions depend on regressors only through a linear index. The estimator permits both discrete and continuous regressors, both discrete and continuous failure times, and can be applied to right‐censored data and to multiple‐risks data, in which case the hazard functions are risk‐specific. The estimator is root‐n consistent and asymptotically normally distributed. The estimator performs well in Monte Carlo experiments. |
