Optimal multiple functional regression analysis using perturbation theory

Autor:	Mehmet Pakdemirli
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	Functional regression perturbation analysis data approximation Science (General) Q1-390
Zdroj:	Journal of Taibah University for Science, Vol 18, Iss 1 (2024)
Druh dokumentu:	article
ISSN:	16583655 1658-3655
DOI:	10.1080/16583655.2024.2366522
Popis:	A regression analysis is presented based on several functions. A normalized data are used which enables the usage of magnitude of orders in perturbation theory. The criteria to eliminate unnecessary base functions are derived with the aid of order of magnitudes in perturbations. The analysis generalizes the previous work on polynomial regression of arbitrary orders. Properties of the regression coefficients are outlined via theorems. Numerical tests are conducted to outline the usage of the analysis to eliminate unnecessary functions and obtain a reasonable approximation of the data in a continuous form.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/2cf7587f2f8f4bd1a78bc3e25b7a862c Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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