The Accuracy and the Computational Complexity of a Multivariate Binned Kernel Density Estimator

Lasse Holmström

Journal of Multivariate Analysis, 2000, vol. 72, issue 2, 264-309

Abstract: The computational cost of multivariate kernel density estimation can be reduced by prebinning the data. The data are discretized to a grid and a weighted kernel estimator is computed. We report results on the accuracy of such a binned kernel estimator and discuss the computational complexity of the estimator as measured by its average number of nonzero terms.

Keywords: Kernel density estimation; binning; estimation error; computational complexity (search for similar items in EconPapers)
Date: 2000
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