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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.

MSC:
62G07 Density estimation
65C60 Computational problems in statistics (MSC2010)
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