Optimal multiple functional regression analysis using perturbation theory
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 general...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Series: | Journal of Taibah University for Science |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/16583655.2024.2366522 |
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| Summary: | 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. |
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| ISSN: | 1658-3655 |