Goodness-of-fit tests for multiple regression with circular response

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UDC.coleccionInvestigaciónes_ES
UDC.departamentoMatemáticases_ES
UDC.grupoInvModelización, Optimización e Inferencia Estatística (MODES)es_ES
dc.contributor.authorMeilán-Vila, Andrea
dc.contributor.authorFrancisco-Fernández, Mario
dc.contributor.authorCrujeiras-Casais, Rosa M.
dc.date.accessioned2023-11-28T19:52:13Z
dc.date.available2023-11-28T19:52:13Z
dc.date.issued2022
dc.descriptionVersión final aceptada de: https://doi.org/10.1080/00949655.2021.2015597es_ES
dc.descriptionThis is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Statistical Computation and Simulation on 2022, available at: https://doi.org/10.1080/00949655.2021.2015597es_ES
dc.description.abstract[Abstract]: Testing procedures for assessing a parametric regression model with a circular response and an Rd-valued covariate are proposed and analysed in this work. The test statistics are based on a circular distance comparing a (non-smoothed or smoothed) parametric circular regression estimator and a nonparametric one. Two bootstrap procedures for calibrating the tests in practice are also presented. Finite sample performance of the tests in different scenarios is analysed by simulations and illustrated with real data examples.es_ES
dc.description.sponsorshipThe authors thank Prof. Felicita Scapini and her 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 the Associate Editor and two anonymous referees for numerous useful comments that significantly improved this article. This research has been partially supported by MINECO (Grants MTM2016-76969-P and MTM2017-82724-R), MICINN (Grant PID2020-113578RB-I00) and by Xunta de Galicia (Grant ED481A-2017/361, through the ESF. Grupos de Referencia Competitiva ED431C-2016-015, ED431C-2017-38 and ED431C-2020-14, and Centro de Investigación del SUG ED431G 2019/01, through the ERDF).es_ES
dc.description.sponsorshipXunta de Galicia; ED481A-2017/361es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2016-015es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2017-38es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2020-14es_ES
dc.description.sponsorshipXunta de Galicia; ED431G 2019/01es_ES
dc.identifier.citationA. Meilán-Vila, M. Francisco-Fernández & R.M. Crujeiras (2022) Goodness-of-fit tests for multiple regression with circular response, Journal of Statistical Computation and Simulation, 92:9, 1941-1963, DOI: 10.1080/00949655.2021.2015597es_ES
dc.identifier.doi10.1080/00949655.2021.2015597
dc.identifier.urihttp://hdl.handle.net/2183/34361
dc.language.isoenges_ES
dc.relation.isversionof10.1080/00949655.2021.2015597
dc.relation.projectIDinfo: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.relation.projectIDinfo: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.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/METODOS ESTADISTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORIA Y APLICACIONESes_ES
dc.relation.urihttps://doi.org/10.1080/00949655.2021.2015597es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectModel checkinges_ES
dc.subjectCircular dataes_ES
dc.subjectLocal linear regressiones_ES
dc.subjectBootstrapes_ES
dc.titleGoodness-of-fit tests for multiple regression with circular responsees_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication68d3430d-8683-4e55-a4ac-2e688b1e3610
relation.isAuthorOfPublication9724fb7a-c0db-4b2f-aa1a-7f79bf9c2064
relation.isAuthorOfPublication.latestForDiscovery68d3430d-8683-4e55-a4ac-2e688b1e3610

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