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Regression function estimation from dependent observations

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  • Burman, Prabir

Abstract

We consider the problem of estimating a regression function with nonrandom design points and dependent errors. We construct a spline estimate of the regression function and obtain its rate of convergence. It turns out that the dependence of the observations is reflected in this rate.

Suggested Citation

  • Burman, Prabir, 1991. "Regression function estimation from dependent observations," Journal of Multivariate Analysis, Elsevier, vol. 36(2), pages 263-279, February.
    • Handle: RePEc:eee:jmvana:v:36:y:1991:i:2:p:263-279
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    Cited by:

    1. Jung Won Hyun & Prabir Burman & Debashis Paul, 2018. "Local Linear Estimation for Spatial Random Processes with Stochastic Trend and Stationary Noise," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(2), pages 369-394, November.
    2. Raheem, S.M. Enayetur & Ahmed, S. Ejaz & Doksum, Kjell A., 2012. "Absolute penalty and shrinkage estimation in partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 874-891.

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