Kernel Estimators of the Failure-Rate Function and Density Estimation: An Analogy
失效率函数的核估计与密度估计：一种类比
In this article we explore methods by which the rate of convergence of the bias and the mean squared error of kernel estimators of the failure-rate function can be improved. We show that if the kernel is not restricted to be nonnegative and is suitably chosen, then the bias contribution to the asymptotic mean squared error can be eliminated to any required order, and the rate of convergence of the asymptotic mean squared error can be brought as close to n −1 as is desired.…