Optimal multiple functional regression analysis using perturbation theory
| dc.contributor.author | Pakdemirli M. | |
| dc.date.accessioned | 2024-07-22T08:01:34Z | |
| dc.date.available | 2024-07-22T08:01:34Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | 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. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. | |
| dc.identifier.DOI-ID | 10.1080/16583655.2024.2366522 | |
| dc.identifier.issn | 16583655 | |
| dc.identifier.uri | http://akademikarsiv.cbu.edu.tr:4000/handle/123456789/11493 | |
| dc.language.iso | English | |
| dc.publisher | Taylor and Francis Ltd. | |
| dc.rights | All Open Access; Gold Open Access | |
| dc.title | Optimal multiple functional regression analysis using perturbation theory | |
| dc.type | Article |