Improving bias in kernel density estimation

For order qq kernel density estimators we show that the constant bqbq in bias=bqhq+o(hq)bias=bqhq+o(hq) can be made arbitrarily small, while keeping the variance bounded. A data-based selection of bqbq is presented and Monte Carlo simulations illustrate the advantages of the method.