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Local polynomial fitting under association

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  • Masry, Elias

Abstract

We consider the estimation of multivariate regression functions r(x1,...,xd) and their partial derivatives up to a total order p[greater-or-equal, slanted]1 using high-order local polynomial fitting. The processes {Yi,Xi} are assumed to be (jointly) associated. Joint asymptotic normality is established for the estimates of the regression function r and all its partial derivatives up to the total order p. Expressions for the bias and variance/covariance matrix (of the asymptotic distribution) are given.

Suggested Citation

  • Masry, Elias, 2003. "Local polynomial fitting under association," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 330-359, August.
    • Handle: RePEc:eee:jmvana:v:86:y:2003:i:2:p:330-359
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    References listed on IDEAS

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    Cited by:

    1. Chen, Jia, 2008. "Asymptotics of kernel density estimators on weakly associated random fields," Statistics & Probability Letters, Elsevier, vol. 78(18), pages 3230-3237, December.
    2. Lin, Zhengyan & Li, Degui, 2007. "Asymptotic normality for L1-norm kernel estimator of conditional median under association dependence," Journal of Multivariate Analysis, Elsevier, vol. 98(6), pages 1214-1230, July.

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