The Strong Consistency for the Estimators of Longitudinal Data in Semiparametric Regression Model with ρ ̃-Mixing Errors

Authors

  • Ping Xiao
  • Xinsheng Liu

DOI:

https://doi.org/10.54097/hset.v31i.5151

Keywords:

ρ ̃-mixing random variables, semiparametric regression model, longitudinal data, Strong consistency, convergence rate.

Abstract

Consider the following semiparametric regression model for longitudinal data with - mixing errors: , where, the response variable and the covariate vector  taken from the -th subject at time ,    is the - mixing random variables,  We establish a strong consistency for the least squares estimator of the parametric  and the estimator of the non-parametric function  under some mild conditions.

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References

Gao J T, Chen X R, Zhao L C. Asymptotic normality of a class of estimators in partial linear models [J]. Acta Math. Sinica, 1994, 37(2): 256-268.

Hu H, Wu L. Convergence rates of wavelet estimators in semiparametric regression models under NA samples [J]. Chinese Annals of Mathematics, Series B, 2012, 33(4): 609-624.

Ping T, Lin Y, Liugen X. Asymptotic properties of estimators in partially linear single-index model for longitudinal data [J]. Acta Mathematica Scientia, 2010, 30(3): 677-687.

Zhou X C, Lin J G. Semiparametric regression estimation for longitudinal data in models with martingale difference error's structure [J]. Statistics, 2013, 47(3): 521-534.

Zhou X, Lin J. Strong consistency of estimators in partially linear models for longitudinal data with mixing-dependent structure [J]. Journal of Inequalities and Applications, 2011, 2011(1): 1-18.

Kolmogorov A N, Rozanov Y A. On strong mixing conditions for stationary Gaussian processes [J]. Theory of Probability & Its Applications, 1960, 5(2): 204-208.

Bradley R C. Equivalent mixing conditions for random fields [J]. The Annals of Probability, 1993, 21(4): 1921-1926.

Wang X, Deng X, Xia F, et al. The consistency for the estimators of semiparametric regression model based on weakly dependent errors [J]. Statistical Papers, 2017, 58(2): 303-318

Sung S H. Complete convergence for weighted sums of-mixing random variables [J]. Discrete Dynamics in Nature and Society, 2010, 2010.

Sung S H. On the strong convergence for weighted sums of random variables [J]. Statistical Papers, 2011, 52(2): 447-454.

Wu Y, Wang C, Volodin A. Limiting behavior for arrays of rowwise ρ*-mixing random variables [J]. Lithuanian Mathematical Journal, 2012, 52(2): 214-221.

Wu Q, Jiang Y. Some strong limit theorems for ρ-mixing sequences of random variables [J]. Statistics & Probability Letters, 2008, 78(8): 1017-1023.

Wu Q, Jiang Y. Chover-type laws of the k-iterated logarithm for ρ-mixing sequences of random variables [J]. Journal of Mathematical Analysis and Applications, 2010, 366(2): 435-443.

Zhu C H. Convergence Rate of the Estimate of the Regression Function under NA Sequence [J]. College Mathematics, 2008, 24(4): 69-75.

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Published

10-02-2023

How to Cite

Xiao, P., & Liu, X. (2023). The Strong Consistency for the Estimators of Longitudinal Data in Semiparametric Regression Model with ρ ̃-Mixing Errors. Highlights in Science, Engineering and Technology, 31, 255-262. https://doi.org/10.54097/hset.v31i.5151