Geodesic
The asymptotic properties for the estimators in a semiparametric regression model based on m-asymptotic negatively associated errors
Filomat, Tome 37 (2023) no. 8, p. 2437

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In this paper, we investigate the parametric component and nonparametric component estimators in a semiparametric regression model based on m-asymptotic negatively associated (m-ANA, for short) random variables. The r-th (r > 1) mean consistency, complete consistency and uniform consistency are obtained under some suitable conditions. In order to assess the finite sample performance, we also present a numerical simulation in the last section of the paper. The results obtained in the paper extend the corresponding ones for independent random errors, φ-mixing and other dependent random errors.
DOI : 10.2298/FIL2308437S
Classification : 62G20
Keywords: Semiparametric regression model, m-ANA random variables, r-th mean consistency, Complete consistency, Uniform consistency 
Wanyue Shao; Yuxin Ye; Miaomaio Wang; Xuejun Wang. The asymptotic properties for the estimators in a semiparametric regression model based on m-asymptotic negatively associated errors. Filomat, Tome 37 (2023) no. 8, p. 2437 . doi: 10.2298/FIL2308437S
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     title = {The asymptotic properties for the estimators in a semiparametric regression model based on m-asymptotic negatively associated errors},
     journal = {Filomat},
     pages = {2437 },
     year = {2023},
     volume = {37},
     number = {8},
     doi = {10.2298/FIL2308437S},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2308437S/}
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