Geodesic
Asymptotic normality of linear regression parameter estimator in the case of random regressors
Teoriâ slučajnyh processov, Tome 21 (2016) no. 1, pp. 17-30

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Sufficient conditions of asymptotic normality of the least squares estimator of linear regression model parameter in the case of discrete time and weak or long-range dependent random regressors and noise are obtained in the paper.
Keywords: Asymptotic normality, least squares estimator, linear regression, random regressors, weak dependence, long-range dependence. 
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     author = {A. V. Ivanov and I. V. Orlovsky},
     title = {Asymptotic normality of linear regression parameter estimator in the case of random regressors},
     journal = {Teori\^a slu\v{c}ajnyh processov},
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     publisher = {mathdoc},
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     url = {http://geodesic.mathdoc.fr/item/THSP_2016_21_1_a2/}
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A. V. Ivanov; I. V. Orlovsky. Asymptotic normality of linear regression parameter estimator in the case of random regressors. Teoriâ slučajnyh processov, Tome 21 (2016) no. 1, pp. 17-30. http://geodesic.mathdoc.fr/item/THSP_2016_21_1_a2/