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

✍ Scribed by Lasse Holmström

Publisher
Elsevier Science
Year
2000
Tongue
English
Weight
475 KB
Volume
72
Category
Article
ISSN
0047-259X

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✦ Synopsis

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.

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