A new class of local linear azard estimators based on weig ted least square kernel estimation is considered. The class includes the kernel Hazard estimator of Ramlau-Hansen (1983), which as tHe same boundary correction property as the local linear regression estimator (see Fan and Gijbels,...

Variable kernel hazard estimators are considered in the case, where the bandwidth is allowed to depend on the exposure. Simulations show, that when the exposure varies substantially, then this can improve the performance of the basic kernel smoother con-siderable. A two-stage approach for kernel...

This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it symptotically...