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This article is cited in 1 scientific paper (total in 1 paper)
General numerical methods
Approximation of functions defined in tabular form: multicriteria approach
A. P. Nelyubina, V. V. Podinovskib a Mechanical Engineering Research Institute, Russian Academy of Sciences, 101990, Moscow, Russia
b National Research University–Higher School of Economics (HSE University), 101000, Moscow, Russia
Abstract:
A new approach to estimating approximation parameters is developed. In this approach, the distance of the approximating function from a given finite set of points is estimated by a vector criterion the components of which are the absolute values of residuals at all points. Using this criterion, the remoteness preference relation is defined, and the nondominated function with respect to this relation is considered to be the best approximating function. Approximation for several preference relations is studied, including the Pareto relation and the relation generated by the information about the equal importance of the criteria. Computational issues are considered and the relationship between the introduced approximating functions and the classical ones (obtained by the methods of least squares, least modulus, and the least maximum absolute value of deviation) are considered.
Key words:
approximation of functions, regression analysis, multicriteria analysis, criteria importance theory.
Received: 08.09.2022 Revised: 29.09.2022 Accepted: 02.02.2023
Citation:
A. P. Nelyubin, V. V. Podinovski, “Approximation of functions defined in tabular form: multicriteria approach”, Zh. Vychisl. Mat. Mat. Fiz., 63:5 (2023), 717–730; Comput. Math. Math. Phys., 63:5 (2023), 730–742
Linking options:
https://www.mathnet.ru/eng/zvmmf11548 https://www.mathnet.ru/eng/zvmmf/v63/i5/p717
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