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Improvement of regression forecasting models

Наименование публикации:Improvement of regression forecasting modelsАвторы:Моисеев Н. А. 
Зубакин В.А., Косоруков О.А.
Тематическая область:Экономика и экономические науки
Вид публикации:Статья в журнале
Электронная публикация:ДаЯзык издания:АнглийскийГод издания:2015Страна издания: Канада Наименование журнала или сборника:Modern Applied ScienceНомер журнала (с указанием года):№6 (2015)Код ISSN или ISBN:1913-184Количество страниц:10Количество печатных листов:0,5Индексация:ScopusБиблиографическая ссылка:Zubakin V.A., Kosorukov O.A., Moiseev N.A. “Improvement of regression forecasting models”. Modern Applied Science. Canada. – 2015. – №9 (6). – P. 344-353Аннотация (реферат):

​​​In this paper authors propose the technique, which decreases average forecast error of regression based models. The main idea of the method is to use the weighted sum of several regression equations, which satisfy Ordinary Least Squares prerequisites and have independent residuals, instead of only one. It is shown that if all method requirements are met, it is possible to decrease Mean Squared Error almost by half, using just three equations. This technique allows deriving equations which contain more predictors than the number of observations. Additionally, this method proves to be more consistent in time than any of regressions, used in it, separately. It is also illustrated, that the proposed method outperforms the regression equation, computed with the same independent variables, and, thus, it gives more accurate estimators of regression coefficients.  Empirical results are provided as well.


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