Abstract
There are several levels of sophistication when specifying the bandwidth matrix H to be used in a multivariate kernel density estimator, including H to be a positive multiple of the identity matrix, a diagonal matrix with positive elements or, in its most general form, a symmetric positive-definite matrix. In this paper, the author proposes a data-based method for choosing the smoothing parametrization to be used in the kernel density estimator. The procedure is fully illustrated by it simulation study and some real data examples.
Type
Publication
Canadian Journal of Statistics
