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The empirical performances of the selection criteria for nonparametric regression using smoothing spline

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dc.contributor.authorAydın, Dursun
dc.contributor.authorOmay, Rabia Ece
dc.contributor.orcid0000-0001-8393-1270
dc.contributor.orcid0000-0002-3819-4563
dc.date.accessioned2025-11-13T21:28:55Z
dc.date.issued2006-11-20
dc.identifier.endpage233
dc.identifier.issn2522-0519
dc.identifier.openalexW2104185612
dc.identifier.startpage228
dc.identifier.urihttps://hdl.handle.net/11421/13581
dc.identifier.urihttp://www.wseas.us/e-library/conferences/2006venice/papers/539-210.pdf
dc.language.isoen
dc.relation.ispartofComputational intelligence
dc.rightsrestrictedAccess
dc.subjectSmoothing
dc.subjectSmoothing spline
dc.subjectNonparametric statistics
dc.subjectSelection (genetic algorithm)
dc.subjectNonparametric regression
dc.subjectSpline (mechanical)
dc.subjectComputer science
dc.subjectMonte Carlo method
dc.subjectMATLAB
dc.subjectMathematical optimization
dc.subjectModel selection
dc.subjectRegression analysis
dc.subjectStatistics
dc.subjectMathematics
dc.subjectMachine learning
dc.subjectSpline interpolation
dc.subjectEngineering
dc.titleThe empirical performances of the selection criteria for nonparametric regression using smoothing spline
dc.typeArticle
dspace.entity.typePublication
local.authorid.openalexA5083004617
local.authorid.openalexA5023425818

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