Abstract: The paper describes methods for assessing the dynamics of predictor significance in a linear regression model, involving either the solution of the quadratic programming problem or the use of the weighted least squares method. On the basis of the second approach, the dynamics of the contributions of independent variables for the model of the volume of loading by Russian railway transport has been estimated. The results of the functioning of alternative modes of transport in relation to the railway transport were used as independent variables: sea, road, inland water and pipeline.
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Keywords and phrases: regression model, quadratic programming problem, weighted least squares method, factor contributions, railway transport.
Received: December 2, 2022; Accepted: December 26, 2022; Published: December 31, 2022
How to cite this article: S. I. Noskov and A. S. Vergasov, Evaluating the dynamics of factor contributions in a regression model of the volume of loading by rail transport in Russia, Advances and Applications in Statistics 84 (2023), 85-90. http://dx.doi.org/10.17654/0972361723006
This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License
References:
[1] N. V. Volkova and T. V. Pozdnyakova, Construction and computer implementation of regression models of population territorial loyalty factors influence on rural economic development, South Siberian Scientific Bulletin 4 1(28) (2019), 234-241. [2] M. L. Agranovich and A. A. Dreneva, Influence of educational parameters on youth unemployment, Scientific Vector of the Balkans 4-4(10) (2020), 59-63. [3] V. P. Nevezhin and M. D. Shuvarikov, Study of factors affecting carbon dioxide emissions, Management Accounting 3-3 (2022), 618-625. [4] S. I. Noskov, Construction of a linear regression model with dynamic parameters, Bulletin of the Technological University 5(25) (2022), 99-101. [5] S. I. Noskov, Comparative assessment of the significance of predictors when using different methods of identifying the parameters of the regression model, News of the Tula State University, Technical Science 9 (2021), 228-230. [6] S. I. Noskov, Evaluation of the dynamics of factor contributions in a linear regression model, Bulletin of the Voronezh State Technical University 5(17) (2021), 15-19. [7] S. I. Noskov and I. P. Vrublevsky, Analysis of the regression model of railway transport cargo turnover, Bulletin of Transport of the Volga Region 1(79) (2020), 86-90. [8] S. I. Noskov and A. A. Khonyakov, Application of the risk function for modeling economic systems, South Siberian Scientific Bulletin 5(33) (2020), 85-92.
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