In this paper we propose a new method for estimating parameters in a single-index model under censoring based on the Beran estimator for the conditional distribution function. This, likelihood-based method is also a useful and simple tool used for bandwidth selection. Additionally, we perform an...

Using Edgeworth expansions we compare the rates of convergence of the normal approximation and two bootstrap approaches for the sample mean of a symmetric population. In a simulation study we see how bad is the Monte Carlo approximation when bootstrapping the Edgeworth expansions.