A new perturbation approach to optimal polynomial regression

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dc.contributor.authorPakdemirli M.
dc.date.accessioned2024-07-22T08:12:05Z
dc.date.available2024-07-22T08:12:05Z
dc.date.issued2016
dc.description.abstractA new approach to polynomial regression is presented using the concepts of orders of magnitudes of perturbations. The data set is normalized with the maximum values of the data first. The polynomial regression of arbitrary order is then applied to the normalized data. Theorems for special properties of the regression coefficients as well as some criteria for determining the optimum degrees of the regression polynomials are posed and proven. The new approach is numerically tested, and the criteria for determining the best degree of the polynomial for regression are discussed. © 2016 by the author; licensee MDPI, Basel, Switzerland.
dc.identifier.DOI-ID10.3390/mca21010001
dc.identifier.issn1300686X
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/15905
dc.language.isoEnglish
dc.publisherMDPI AG
dc.rightsAll Open Access; Gold Open Access; Green Open Access
dc.subjectRegression analysis
dc.subjectArbitrary order
dc.subjectOrders of magnitude
dc.subjectPerturbation Analysis
dc.subjectPerturbation approach
dc.subjectPolynomial regression
dc.subjectRegression coefficient
dc.subjectRegression polynomials
dc.subjectSpecial properties
dc.subjectPolynomials
dc.titleA new perturbation approach to optimal polynomial regression
dc.typeArticle

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