Using non-stochastic terms to advantage in kernel-based estimation of integrated squared density derivatives. (English) Zbl 0724.62040
Summary: Improved kernel-based estimates of integrated squared density derivatives are obtained by reinstating non-stochastic terms that have previously been omitted, and using the bandwidth to (approximately) cancel these positive quantities with the leading smoothing bias terms which are negative. Such estimators have exhibited great practical merit in the context of data-based selection of the bandwidth in kernel density estimation.
Keywords:
bandwidth selection; bias reduction; functional estimation; rates of convergence; Improved kernel-based estimates of integrated squared density derivatives; smoothing; kernel density estimationReferences:
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