  In the this paper, the authors propose to estimate the density of a targeted
population with a weighted kernel density estimator (wKDE) based on a weighted
sample. Bandwidth selection for wKDE is discussed. Three mean integrated
squared error based bandwidth estimators are introduced and their performance
is illustrated via Monte Carlo simulation. The least-squares cross-validation
method and the adaptive weight kernel density estimator are also studied. The
authors also consider the boundary problem for interval bounded data and apply
the new method to a real data set subject to informative censoring.
