APPROXIMATION OF TABULATED FUNCTIONS: A MULTI-CRITERIA APPROACH. PART II
- Authors: Nelyubin A.P1, Podinovsky V.V2
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Affiliations:
- Institute for problems in mechanical engineering, Russian Academy of Sciences
- HSE University
- Issue: Vol 65, No 4 (2025)
- Pages: 426–433
- Section: General numerical methods
- URL: https://journals.rcsi.science/0044-4669/article/view/295412
- DOI: https://doi.org/10.31857/S0044466925040022
- EDN: https://elibrary.ru/ICOHDU
- ID: 295412
Cite item
Abstract
The article continues the development of a new approach to evaluate approximation parameters, in which the distance of the approximating function from the given finite set of points is estimated by a vector criterion, its components are the modules of residuals at all points. The vector criterion is used to define the distance preference ratio, and the best approximation function is considered to be nondominant with respect to this ratio. Compared to the first article of the authors (“Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki”, 2022), which is devoted to parametric methods, the present article offers nonparametric methods for several preference relations, including the Pareto relation and the relation generated by the information about the equality of criteria. Computational problems are considered and the relations between the introduced approximating functions and classical ones are investigated. Calculated examples are provided.
About the authors
A. P Nelyubin
Institute for problems in mechanical engineering, Russian Academy of Sciences
Email: nelubin@gmail.com
Moscow, Russia
V. V Podinovsky
HSE University
Email: podinovski@mail.ru
Moscow, Russia
References
- Демидович Б.П., Марон И.А., Шувалова Э.З. Численные методы анализа. Приближение функций, дифференциальные и интегральные уравнения. М.: Наука, 1967.
- Нелюбин А.П., Подиновский В.В. Аппроксимация таблично заданных функций: многокритериальный подход // Ж. вычисл. матем. и матем. физ. 2023. Т. 63. № 5. С. 717–730.
- Анатольев С. Непараметрическая регрессия // Квантиль. 2009. № 7. С. 37–52.
- NIST/SEMATECH e-Handbook of Statistical Methods. http://www.itl.nist.gov/div898/handbook
- Малов С.В. Регрессионный анализ: теоретические основы и практические рекомендации. СПб.: Изд-во Санкт-Петербургского ун-та, 2013.
- Подиновский В.В., Подиновская О.В. Новые многокритериальные решающие правила в теории важности критериев // Докл. АН. 2013. Т. 451. № 1. С. 21–23.
- Fishburn P.C. Decision and Value Theory. New York: Wiley, 1964.
- Podinovski V.V. On the use of importance information in MCDA problems with criteria measured on the first ordered metric scale // J. Multi-Criteria Decision Analys. 2009. V. 15. P. 163–174.
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