Keywords and phrases: regression model, parameter estimation, least squares methods, moduli, anti-robust estimation.
Received: March 23, 2021; Accepted: April 22, 2021; Published: June 26, 2021
How to cite this article: S. I. Noskov and A. S. Vergasov, Choosing a regression model for the transportation of goods in Russia, Advances and Applications in Statistics 69(1) (2021), 1-5. DOI: 10.17654/AS069010001
This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License
References:
[1] S. I. Noskov and A. A. Khonyakov, Applying the risk function to model economic systems, South-Siberian Scientific Bulletin 33(5) (2020), 85-92. [2] S. I. Noskov, Object modeling technology with unstable operation and data uncertainty, Federal State Public Educational Establishment of Higher Training Eastern Siberia Institute of the Ministry of the Interior of the Russian Federation, 110, Lermontov Street, Irkutsk, 1996, pp. 320. [3] S. I. Noskov, The criterion of “consistency of behavior” in regression analysis, Modern Technologies, System Analysis, Modeling 37(1) (2013), 107-110. [4] S. I. Noskov and A. V. Baenkhaeva, Multiple estimation of parameters for the linear regression equation, Modern Technologies, System Analysis, Modeling 3 (2016), 133-138. [5] V. B. Golovchenko and S. I. Noskov, Estimation of an econometric model using statistical data and expert information, Avtomatika i telemehanika 4 (1991), 123-132. [6] S. I. Noskov and V. A. Protopopov, Assessment of the level of vulnerability of the objects of transport infrastructure: a formalized approach, Modern Technologies, System Analysis, Modeling 32(4) (2011), 241-244. [7] A. V. Lakeyev and S. I .Noskov, Description of the solution set to linear equation with the intervally defined operator and right-hand side, Doklady Mathematics 330(4) (1993), 430. [8] S. I. Noskov and I. P. Vrublevsky, Railway transport functioning the regression model performance indicators dynamics, Modern Technologies, System Analysis, Modeling 50(2) (2016), 192-197. [9] M. P. Bazilevskiy, I. P. Vrublevskiy, S. I. Noskov and I. S. Yakovchuk, Medium-term forecasting of performance indicators of functioning of krasnoyarsk railway, Fundamental Research 10(3) (2016), 471-476. [10] A. V. Baenkhaeva, M. P. Bazilevskiy and S. I. Noskov, Modeling of gross regional product Irkutsk region on the basis of methods of multiple estimation of regression parameters, Fundamental Research 10(1) (2016), 9-14. [11] S. I. Noskov, Parameters estimation of the fitting functions with constant proportions, Modern Technologies, System Analysis, Modeling 38(2) (2013), 135-136. [12] M. P. Bazilevskiy and S. I. Noskov, Formalization of the problem of construction of linear multiplicative regressions in the form of a partial-boolean linear programming problem, Modern Technologies, System Analysis, Modeling 55(3) (2017), 101-105. [13] M. P. Bazilevskiy and S. I. Noskov, Program complex for linear regression model construction considering behavior consistency criterion of actual and calculated trajectories of explained variable value change, Bulletin of the Irkutsk State Technical University 128(9) (2017), 37-44. [14] S. I. Noskov, O. V. Bukova, O. E. Nekipelova and L. E. Sokolova, Possible way of search of the compromise solution in a problem of linear programming with multi-criterion function, Fundamental Research 6(3) (2014), 502-505. [15] V. B. Golovchenko and S. I. Noskov, The class of linear regression parameters on the basis of expert statements, Cybernetics and System Analysis 5 (1992), 109-115. [16] V. B. Golovchenko and S. I. Noskov, Estimation of an econometric model using statistical data and expert information, Automation and Remote Control 4 (1991), 542-548. [17] S. I. Noskov and M. P. Bazilevskiy, On index transformations of matrices in regression models construction, Information Technologies and Mathematical Modeling in the Control of Complex Systems 3(4) (2019), 11-16. [18] S. I. Noskov, Method of antirobast estimation of linear regression parameters: number of maximum on the module of approximation errors, South-Siberian Scientific Bulletin 29(1) (2020), 51-54. [19] S. I. Noskov and M. P. Bazilevskiy, Multiple parameter estimation and behavior consistency criterion in regression analysis, Bulletin of the Irkutsk State Technical University 135(4) (2018), 101-110. [20] M. P. Bazilevskiy and S. I. Noskov, The algorithm for a linear-multiplicative regression construction, Modern Technologies, System Analysis, Modeling 29(1) (2011), 88-92. [21] M. P. Bazilevskiy and S. I. Noskov, Algorithm for forming a set of regression models by means of conversion of a dependent variable, International Journal of Applied and Fundamental Research 1 (2011), 159-160. [22] S. I. Noskov, A. S. Vergasov, V. O. Zayanchukovskaya and N. I. Gluhov, Interval regression models of a machine-building enterprise, IOP Conference Series: Materials Science and Engineering, Krasnoyarsk Science and Technology City Hall of the Russian Union of Scientific and Engineering Associations Krasnoyarsk, Russia, 2020, 42026. [23] S. I. Noskov and A. S. Vergasov, Application criterion of displacement when choosing the method of evaluating the parameters of regression equations, Advances and Applications in Statistics 61(1) (2020), 89-94.
|