Теорема про достатню умову рівності оцінок МНК та Ейткена старшого коефіцієнту квадратичної регресії: Fìz.-mat. model. ìnf. tehnol. 2021, 33:138-142

At the paper in the case of heteroscedastic independent deviations a quadratic regression model is studied. A theorem is formulated that gives a sufficient condition on the variance of deviations for the coincidence of Aitken's estimate of the leading regression coefficient with his estimation...

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Bibliographic Details
Date:2021
Main Author: Savkina, Marta
Format: Article
Language:Ukrainian
Published: Інститут прикладних проблем механіки і математики ім. Я. С. Підстригача НАН України 2021
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Online Access:https://www.fmmit.lviv.ua/index.php/fmmit/article/view/217
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Journal Title:Physico-mathematical modeling and informational technologies

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Physico-mathematical modeling and informational technologies
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Summary:At the paper in the case of heteroscedastic independent deviations a quadratic regression model is studied. A theorem is formulated that gives a sufficient condition on the variance of deviations for the coincidence of Aitken's estimate of the leading regression coefficient with his estimation of the OLS in the case of an odd number of observation points and a bisymmetric covariance matrix. On the basis of this theorem, in some cases examples of non-unit covariance matrices are constructed for which the indicated estimations of the leading coefficient of the quadratic regression coindcide. References Demidenko, E. Z. (1981). Linejnaya i nelinejnaya regressii. M.:Finansy i statistika. Anderson, T. (1976). Statisticheskij analiz vremennyh ryadov. M.: Mir. Seber, Dzh. (1980). Linejnyj regressionnyj analіz. M.: Mir. Savkina, M. Yu. (2020). Dostatnia umova zbihu otsinok MNK ta Eitkena parametru kvadratychnoi rehre-sii u vypadku heteroskedastychnykh vidkhylen. Zhurnal obchysliuvalnoi ta prykladnoi matematyky, 2(134), 45-58. Savkina, M. Yu. (2019). Umovy zbihu otsinok MNK ta Eitkena parametriv modeli kvadratychnoi rehresii. Zhurnal obchysliuvalnoi ta prykladnoi matematyky, 3(132), 33-42.
DOI:10.15407/fmmit2021.33.138