Multivariate Density Estimation with General Flat-Top Kernels of Infinite Order,
The problem of nonparametric estimation of a multivariate density function is addressed. In particular, a general class of estimators with favorable asymptotic performance (bias, variance, rate of convergence) is proposed. The proposed estimators are characterized by the flatness near the origin of the Fourier transform of the kernel and are actually shown to be exactly-consistent provided the density is sufficiently smooth.
Year of publication: |
1999
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Authors: | Politis, Dimitris N. ; Romano, Joseph P. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 68.1999, 1, p. 1-25
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Publisher: |
Elsevier |
Keywords: | bias reduction Fourier transform kernel mean squared error nonparametric density estimation rate of convergence smoothing |
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