Noskov S.I. Formulation of the problem of estimating regression parameters by minimizing the vector loss function specified on observation groups // Informacionnye tehnologii i matematicheskoe modelirovanie v upravlenii slozhnymi sistemami: ehlektronnyj nauchnyj zhurnal [Information technology and mathematical modeling in the management of complex systems: electronic scientific journal], 2022. No. 3(15). P. 58-60. DOI: 10.26731/2658-3704.2022.3(15).58-60 [Accessed 15/10/22]
10.26731/2658-3704.2022.3(15).58-60
The paper formulates the problem of estimating the parameters of a regression equation of a general form by minimizing the vector loss function, the components of which are particular and differing loss functions given in different parts of the processed data sample.
1. Demidenko E.Z. Linear and non-linear regression. - M.: Finance and statistics, 1981. 302p.
2. Kamenev G.K. Multicriteria method of identification sets // Zh. Vychisl.mat. and mat. physics.- 2016.- v.56.- №11.- Р.1872-1888.
3. Kamenev G.K. Multi-criteria method of identification and forecasting // Mathematical Modeling. – 2017.- No. 8.- P.29-43.
4. Noskov S.I. Compromise Pareto estimates of linear regression parameters // Mathematical Modeling. - 2020. - v.32.- No. 11.- Р. 70–78.
5. Baenkhaeva A.V., Bazilevsky M.P., Noskov S.I. Software complex for multiple estimation of regression models // Information technologies and problems of mathematical modeling of complex systems. - 2016. - No. 17. - P. 38–44.
6. Noskov S.I. L-set in the multicriteria problem of estimating the parameters of regression equations // Information technologies and problems of mathematical modeling of complex systems.- 2004.- №1.- P.64-71.
7. Noskov S.I. Technology for modeling objects with unstable operation and uncertainty in data. - Irkutsk: Oblinformpress. - 1996. - 320 p.