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The accuracy and the computational complexity of a multivariate binned kernel density estimator. (English) Zbl 1065.62511
Summary: 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.

62G07 Density estimation
65C60 Computational problems in statistics (MSC2010)
Full Text: DOI
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