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An exponential inequality and its application to M estimators in multiple linear models

Author

Listed:
  • Xin Deng

    (Anhui University)

  • Xuejun Wang

    (Anhui University)

Abstract

In the paper, an exponential inequality for widely orthant dependent random variables is established without bounded condition. By using the inequality, we further investigate the strong linear representation for the M estimator of the regression parameter vector in linear regression models with widely orthant dependent random errors under some general conditions. In addition, we have conducted comprehensive simulation studies to demonstrate the validity of obtained theoretical results.

Suggested Citation

  • Xin Deng & Xuejun Wang, 2020. "An exponential inequality and its application to M estimators in multiple linear models," Statistical Papers, Springer, vol. 61(4), pages 1607-1627, August.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:4:d:10.1007_s00362-018-0994-0
    DOI: 10.1007/s00362-018-0994-0
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    References listed on IDEAS

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    1. Xuejun Wang & Zeyu Si, 2015. "Complete consistency of the estimator of nonparametric regression model under ND sequence," Statistical Papers, Springer, vol. 56(3), pages 585-596, August.
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