We show how to smoothly 'monotonise" standard kernel estimators of hazard rate using bootstrap weights. Our method takes a variety of forms, depending on the choice of kernel estimator and on the distance function used to defie a certain constrained optimisation problem.

In this paper the interest is in testing whether a regression function is polynomial of a certain degree. One possible approach to this testing problem is to do a parametric polynomial fit and a nonparametric fit and to reject the null hypothesis of a polynomial function if the distance between...

This paper further examines the bootstrap method proposed by Simar and Wilson (1998) for DEA efficiency estimators. Some simplifications are provided, and we provide Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method.

A consistent estimator for the spectral density of a stationary random process can be obtained by smoothing the periodigrams across frequency. An important component of smoothing is the choice of the span. In this paper, we propose a span selector originally developed for use in fitting...

This paper further examines the bootstrap method proposed by Simar and Wilson (1998) for DEA efficiency estimators. Some simplifications are provided, and we provide Monte Carlo evidence on the coverage probabilities of confidence intervals estimated by the method.