Receipt date: 
Bibliographic description of the article: 

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]

Journal number: 


Article File: 

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. 

List of references: 

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.