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Nonparametric multiple regression estimation for circular response

dc.contributor.authorMeilán-Vila, Andrea
dc.contributor.authorFrancisco-Fernández, Mario
dc.contributor.authorCrujeiras-Casais, Rosa M.
dc.contributor.authorPanzera, Agnese
dc.date.accessioned2023-11-24T15:39:19Z
dc.date.available2023-11-24T15:39:19Z
dc.date.issued2021
dc.identifier.citationMeilán-Vila, A., Francisco-Fernández, M., Crujeiras, R.M. et al. Nonparametric multiple regression estimation for circular response. TEST 30, 650–672 (2021). https://doi.org/10.1007/s11749-020-00736-wes_ES
dc.identifier.urihttp://hdl.handle.net/2183/34329
dc.descriptionVersión final aceptada de: https://doi.org/10.1007/s11749-020-00736-wes_ES
dc.descriptionThis version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect postacceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s11749-020-00736-wes_ES
dc.description.abstractNonparametric estimators of a regression function with circular response and -valued predictor are considered in this work. Local polynomial estimators are proposed and studied. Expressions for the asymptotic conditional bias and variance of these estimators are derived, and some guidelines to select asymptotically optimal local bandwidth matrices are also provided. The finite sample behavior of the proposed estimators is assessed through simulations, and their performance is also illustrated with a real data set.es_ES
dc.description.sponsorshipThe authors acknowledge the support from the Xunta de Galicia Grant ED481A-2017/361 and the European Union (European Social Fund—ESF). This research has been partially supported by MINECO Grants MTM2016-76969-P and MTM2017-82724-R, and by the Xunta de Galicia (Grupo de Referencia Competitiva ED431C-2017-38, and Centro de Investigación de Galicia “CITIC” ED431G 2019/01), all of them through the ERDF. The authors thank Prof. Felicita Scapini and his research team who kindly provided the sand hoppers data that are used in this work. Data were collected within the Project ERB ICI8-CT98-0270 from the European Commission, Directorate General XII Science. The authors also thank two anonymous referees for numerous useful comments that significantly improved this article.es_ES
dc.description.sponsorshipXunta de Galicia; ED481A-2017/361es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2017-38es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.language.isoenges_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2016-76969-P/ES/MODELIZACION NO PARAMETRICA DE DINAMICAS Y DEPENDENCIAS EN SISTEMAS COMPLEJOSes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSIONes_ES
dc.relation.isversionofhttps://doi.org/10.1007/s11749-020-00736-w
dc.relation.urihttps://link.springer.com/article/10.1007/s11749-020-00736-wes_ES
dc.rightsTodos os dereitos reservados. All rights reserved.es_ES
dc.subjectLinear–circular regressiones_ES
dc.subjectMultiple regressiones_ES
dc.subjectLocal polynomial estimatorses_ES
dc.titleNonparametric multiple regression estimation for circular responsees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1007/s11749-020-00736-w


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