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Robust nonparametric regression in time series

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  • Truong, Young K.

Abstract

Consider a stationary time series (Xt, Yt), t = 0, ±1, ... with Xt being d-valued and Yt real-valued. Let [psi](·) denote a monotone function and let [theta](·) denote the robust conditional location functional so that E[[psi](Y0 - [theta](X0))X0] = 0. Given a finite realization (X1, Y1), ..., (Xn, Yn), the problem of estimating [theta](·) is considered. Under appropriate regularity conditions, it is shown that a sequence of the robust conditional location functional estimators can be chosen to achieve the optimal rate of convergence n-1/(2 + d) both pointwise and in Lq (1

Suggested Citation

  • Truong, Young K., 1992. "Robust nonparametric regression in time series," Journal of Multivariate Analysis, Elsevier, vol. 41(2), pages 163-177, May.
    • Handle: RePEc:eee:jmvana:v:41:y:1992:i:2:p:163-177
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    Cited by:

    1. Peng, Liang & Yao, Qiwei, 2004. "Nonparametric regression under dependent errors with infinite variance," LSE Research Online Documents on Economics 22874, London School of Economics and Political Science, LSE Library.
    2. Cai, Zongwu, 2003. "Nonparametric estimation equations for time series data," Statistics & Probability Letters, Elsevier, vol. 62(4), pages 379-390, May.

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