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A nonparametric measure of independence under a hypothesis of independent components

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  • Rosenblatt, Murray
  • Wahlen, Bruce E.
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    Abstract

    Asymptotic normality is derived for a nonparametric measure of independence of the components of random two-vectors. This result is obtained without the restrictive assumptions previuosly made on rate of convergence of the bandwidth sequence of the density estimates used.

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    File URL: http://www.sciencedirect.com/science/article/B6V1D-45DHJ87-3D/2/77f5f877aed580d4f95b152bd716139d
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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 15 (1992)
    Issue (Month): 3 (October)
    Pages: 245-252

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    Handle: RePEc:eee:stapro:v:15:y:1992:i:3:p:245-252

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    Related research

    Keywords: Nonparametric test of independence density function estimate kernel;

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    Cited by:
    1. Pinkse, Joris, 1998. "A consistent nonparametric test for serial independence," Journal of Econometrics, Elsevier, vol. 84(2), pages 205-231, June.
    2. Cees Diks & Valentyn Panchenko, 2005. "Nonparametric Tests for Serial Independence Based on Quadratic Forms," Tinbergen Institute Discussion Papers 05-076/1, Tinbergen Institute.

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