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The strong consistency of M-estimators in linear models

Author

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  • Cheng, Ching-Shui
  • Li, Ker-Chau

Abstract

The strong consistency of M-estimators in linear models is considered. Under some conditions on the ratios of maximum and minimum eigenvalues of the information matrices the desired result is established.

Suggested Citation

  • Cheng, Ching-Shui & Li, Ker-Chau, 1984. "The strong consistency of M-estimators in linear models," Journal of Multivariate Analysis, Elsevier, vol. 15(1), pages 91-98, August.
    • Handle: RePEc:eee:jmvana:v:15:y:1984:i:1:p:91-98
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    Citations

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    Cited by:

    1. Yuan, Ke-Hai & Jennrich, Robert I., 1998. "Asymptotics of Estimating Equations under Natural Conditions," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 245-260, May.
    2. Xin Deng & Xuejun Wang, 2018. "Asymptotic Property of M Estimator in Classical Linear Models Under Dependent Random Errors," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1069-1090, December.
    3. Yuan, Ke-Hai, 1997. "A Theorem on Uniform Convergence of Stochastic Functions with Applications," Journal of Multivariate Analysis, Elsevier, vol. 62(1), pages 100-109, July.
    4. 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.

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