On foundations of estimation for nonparametric regression with continuous optimization

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dc.contributor.authorTaylan, Pakize
dc.date.accessioned2024-04-24T17:58:18Z
dc.date.available2024-04-24T17:58:18Z
dc.date.issued2019
dc.departmentDicle Üniversitesi, Fen Fakültesi, Matematik Bölümüen_US
dc.description.abstractThe aim of parametric regression models like linear regression and nonlinear regression are to produce a reasonable relationship between response and independent variables based on the assumption of linearity and predetermined nonlinearity in the regression parameters by finite set of parameters. Nonparametric regression techniques are widely-used statistical techniques, and they not only relax the assumption of linearity in the regression parameters, but they also do not need a predetermined functional form as nonlinearity for the relationship between response and independent variables. It is capable of handling higher dimensional problem and sizes of sample than regression that considers parametric models because the data should provide both the model building and the model estimates. For this purpose, firstly, PRSS problems for MARS, ADMs, and CR will be constructed. Secondly, the solution of the generated problems will be obtained with CQP, one of the famous methods of convex optimization, and these solutions will be called CMARS, CADMs, and CKR, respectively.en_US
dc.identifier.citationTaylan, P. (2019). On foundations of estimation for nonparametric regression with continuous optimization. Handbook of Research on Big Data Clustering and Machine Learning, 177-203.
dc.identifier.doi10.4018/978-1-7998-0106-1.ch009
dc.identifier.endpage203en_US
dc.identifier.isbn9781799801078
dc.identifier.isbn9781799801061
dc.identifier.scopus2-s2.0-85126074321
dc.identifier.scopusqualityN/A
dc.identifier.startpage177en_US
dc.identifier.urihttps://doi.org/10.4018/978-1-7998-0106-1.ch009
dc.identifier.urihttps://hdl.handle.net/11468/23815
dc.indekslendigikaynakScopus
dc.language.isoenen_US
dc.publisherIGI Globalen_US
dc.relation.ispartofHandbook of Research on Big Data Clustering and Machine Learning
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleOn foundations of estimation for nonparametric regression with continuous optimizationen_US
dc.titleOn foundations of estimation for nonparametric regression with continuous optimization
dc.typeBook Chapteren_US

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