Smoothing histograms by means of lattice-and continuous distributions

Summary Using lattice distributions or an auxiliary density function each satisfying certain moment conditions a general type of estimator for a one dimensional density functionf is developed. This estimator can be looked at as a smoothed histogram. As a measure of quality the exact order of magnitude for the mean squared error is established (pointwise and uniformly) in terms of the size of an iid sample drawn fromf and depending on a design parameter. The methods in deriving the asymptotic behaviour of the mean squared error are based on Edgeworth expansions for the auxiliary distributions.