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Weak consistency of M-estimator in linear regression model with asymptotically almost negatively associated errors

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  • Yu Zhang
  • Xinsheng Liu
  • Hongchang Hu

Abstract

This paper studies a linear regression model with asymptotically almost negatively associated (AANA, in short) random errors. Under some mild conditions, the weak consistency of M-estimator of the unknown parameter is investigated, which extend the corresponding results for independent random errors and negatively associated (NA, in short) random errors. At last, two simulation examples are presented to verify the weak consistency of M-estimator in the model.

Suggested Citation

  • Yu Zhang & Xinsheng Liu & Hongchang Hu, 2020. "Weak consistency of M-estimator in linear regression model with asymptotically almost negatively associated errors," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(11), pages 2800-2816, June.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:11:p:2800-2816
    DOI: 10.1080/03610926.2019.1584307
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    Cited by:

    1. Yu Zhang, 2023. "Asymptotic Normality of M-Estimator in Linear Regression Model with Asymptotically Almost Negatively Associated Errors," Mathematics, MDPI, vol. 11(18), pages 1-16, September.

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