The performance of multivariate kernel density estimates depends crucially on the choice of bandwidth matrix, but progress towards developing good bandwidth matrix selectors has been relatively slow.
We tackle the problem of high-dimensional nonparametric density estimation by taking the class of log-concave densities on ℝp and incorporating within it symmetry assumptions, which facilitate ...
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