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On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models With Symmetric Errors

dc.contributor.author Mahmoudi, M.R.
dc.contributor.author Baleanu, D.
dc.contributor.author Maleki, M.
dc.contributor.author Ji-jun, P.
dc.date.accessioned 2020-03-27T08:03:43Z
dc.date.accessioned 2025-09-18T12:10:05Z
dc.date.available 2020-03-27T08:03:43Z
dc.date.available 2025-09-18T12:10:05Z
dc.date.issued 2019
dc.description.abstract In many real world problems, science fields such as biology, computer science, data mining, electrical and mechanical engineering, and signal processing, researchers aim to compare and classify several regression models. In this paper, a computational approach, based on the non-parametric methods, is used to investigate the similarities, and to classify several linear and non-linear regression models with symmetric errors. The ability of each given approach is then evaluated using simulated and real world practical datasets. © 2019 by the authors. en_US
dc.identifier.citation Pan, Ji-Jun...et al. (2019). "On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models with Symmetric Errors", Symmetry-Basel, Vol. 11, No. 6. en_US
dc.identifier.doi 10.3390/sym11060820
dc.identifier.issn 2073-8994
dc.identifier.scopus 2-s2.0-85068070168
dc.identifier.uri https://doi.org/10.3390/sym11060820
dc.identifier.uri https://hdl.handle.net/20.500.12416/11614
dc.language.iso en en_US
dc.publisher MDPI AG en_US
dc.relation.ispartof Symmetry en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Comparison en_US
dc.subject Friedman Test en_US
dc.subject Linear Regression en_US
dc.subject Nonlinear Regression en_US
dc.subject Sign Test en_US
dc.subject Symmetric Errors en_US
dc.subject Wilcoxon Test en_US
dc.title On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models With Symmetric Errors en_US
dc.title On Comparing and Classifying Several Independent Linear and Non-Linear Regression Models with Symmetric Errors tr_TR
dc.type Article en_US
dspace.entity.type Publication
gdc.author.scopusid 57209536352
gdc.author.scopusid 56684432000
gdc.author.scopusid 7005872966
gdc.author.scopusid 57214767247
gdc.author.yokid 56389
gdc.bip.impulseclass C3
gdc.bip.influenceclass C4
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department Çankaya University en_US
gdc.description.departmenttemp Ji-jun P., College of Mathematics, Dianxi Science and Technology, Normal University, Lincang, 677000, China; Mahmoudi M.R., Department of Statistics, Faculty of Science, Fasa University, Fasa, 74616 86131, Iran; Baleanu D., Department of Mathematics, Faculty of Art and Sciences, Cankaya University Balgat, Ankara, 06530, Turkey; Maleki M., Department of Statistics, Faculty of Science, Shiraz University, Shiraz, 71946 85115, Iran en_US
gdc.description.issue 6 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q2
gdc.description.volume 11 en_US
gdc.description.wosquality Q2
gdc.identifier.openalex W2950535287
gdc.index.type Scopus
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 33.0
gdc.oaire.influence 4.400084E-9
gdc.oaire.isgreen false
gdc.oaire.keywords comparison; Friedman test; linear regression; nonlinear regression; sign test; symmetric errors; Wilcoxon test
gdc.oaire.popularity 2.7693973E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0101 mathematics
gdc.oaire.sciencefields 01 natural sciences
gdc.openalex.collaboration International
gdc.openalex.fwci 4.06165878
gdc.openalex.normalizedpercentile 0.95
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 45
gdc.plumx.crossrefcites 45
gdc.plumx.mendeley 18
gdc.plumx.scopuscites 47
gdc.publishedmonth 6
gdc.scopus.citedcount 47
gdc.virtual.author Baleanu, Dumitru
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