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The asymptotic properties of the estimators in a semiparametric regression model

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Listed:
  • Xuejun Wang

    (Anhui University)

  • Meimei Ge

    (Chuzhou University)

  • Yi Wu

    (Anhui University)

Abstract

In this paper, we investigate the parametric component and nonparametric component estimators in a semiparametric regression model based on $$\varphi $$ φ -mixing random variables. The rth mean consistency, complete consistency, uniform rth mean consistency and uniform complete consistency are established under some suitable conditions. In addition, a simulation to study the numerical performance of the consistency of the nearest neighbor weight function estimators is provided. The results obtained in the paper improve the conditions in the literature and generalize the existing results of independent random errors to the case of $$\varphi $$ φ -mixing random errors.

Suggested Citation

  • Xuejun Wang & Meimei Ge & Yi Wu, 2019. "The asymptotic properties of the estimators in a semiparametric regression model," Statistical Papers, Springer, vol. 60(6), pages 2087-2108, December.
    • Handle: RePEc:spr:stpapr:v:60:y:2019:i:6:d:10.1007_s00362-017-0910-z
    DOI: 10.1007/s00362-017-0910-z
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    References listed on IDEAS

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    1. Shao, Qi-Man, 1993. "Almost sure invariance principles for mixing sequences of random variables," Stochastic Processes and their Applications, Elsevier, vol. 48(2), pages 319-334, November.
    2. Soo Sung, 2011. "On the strong convergence for weighted sums of random variables," Statistical Papers, Springer, vol. 52(2), pages 447-454, May.
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