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Asymptotic normality of linear regression parameter estimator in the case of random regressors
A. V. Ivanov, I. V. Orlovsky National technical university of Ukraine ”KPI”, Department of mathematical analysis
and probability theory, Peremogi avenue 37, Kiev, Ukraine
Аннотация:
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.
Ключевые слова:
Asymptotic normality, least squares estimator, linear regression, random regressors, weak dependence, long-range dependence.
Образец цитирования:
A. V. Ivanov, I. V. Orlovsky, “Asymptotic normality of linear regression parameter estimator in the case of random regressors”, Theory Stoch. Process., 21(37):1 (2016), 17–30
Образцы ссылок на эту страницу:
https://www.mathnet.ru/rus/thsp117 https://www.mathnet.ru/rus/thsp/v21/i1/p17
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Страница аннотации: | 161 | PDF полного текста: | 62 | Список литературы: | 38 |
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