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On near neighbour estimates of a multivariate density

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  • Hall, Peter

Abstract

A recent paper by Mack and Rosenblatt (J. Multivar. Anal. 9 (1979), 1-15) has shown that near neighbour estimators of a density may perform more poorly than other kernel-type estimators, particularly for x values in the tail of a distribution. In order to overcome the difficulties discovered by Mack and Rosenblatt, a generalized type of near neighbour estimator is proposed. Here the window size, or bandwidth, is chosen as a function of near neighbour distances, rather than actually equal to one of the distances. Two forms for this function are suggested and it is proved that for large samples the resulting estimator does not suffer the drawbacks of the usual near neighbour estimator.

Suggested Citation

  • Hall, Peter, 1983. "On near neighbour estimates of a multivariate density," Journal of Multivariate Analysis, Elsevier, vol. 13(1), pages 24-39, March.
    • Handle: RePEc:eee:jmvana:v:13:y:1983:i:1:p:24-39
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    Cited by:

    1. Dai, J. & Sperlich, S., 2010. "Simple and effective boundary correction for kernel densities and regression with an application to the world income and Engel curve estimation," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2487-2497, November.
    2. Aya-Moreno, Carlos & Geenens, Gery & Penev, Spiridon, 2018. "Shape-preserving wavelet-based multivariate density estimation," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 30-47.
    3. Jones, M. C., 1995. "On two recent papers of Y. Kanazawa," Statistics & Probability Letters, Elsevier, vol. 24(3), pages 269-271, August.

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