Mostrar o rexistro simple do ítem
Nonparametric estimation of circular trend surfaces with application to wave directions
dc.contributor.author | Meilán-Vila, Andrea | |
dc.contributor.author | Crujeiras-Casais, Rosa M. | |
dc.contributor.author | Francisco-Fernández, Mario | |
dc.date.accessioned | 2023-11-24T16:15:29Z | |
dc.date.available | 2023-11-24T16:15:29Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Meilán-Vila, A., Crujeiras, R.M. & Francisco-Fernández, M. Nonparametric estimation of circular trend surfaces with application to wave directions. Stoch Environ Res Risk Assess 35, 923–939 (2021). https://doi.org/10.1007/s00477-020-01919-5 | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/34330 | |
dc.description | Versión final aceptada de: https://doi.org/10.1007/s00477-020-01919-5 | es_ES |
dc.description | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/s00477-020-01919-5 | es_ES |
dc.description.abstract | In oceanography, modeling wave fields requires the use of statistical tools capable of handling the circular nature of the data measurements. An important issue in ocean wave analysis is the study of height and direction waves, being direction values recorded as angles or, equivalently, as points on a unit circle. Hence, reconstruction of a wave direction field on the sea surface can be approached by the use of a linear–circular regression model, viewing wave directions as a realization of a circular spatial process whose trend should be estimated. In this paper, we consider a spatial regression model with a circular response and several real-valued predictors. Nonparametric estimators of the circular trend surface are proposed, accounting for the (unknown) spatial correlation. Some asymptotic results about these estimators as well as some guidelines for their practical implementation are also given. The performance of the proposed estimators is investigated in a simulation study. An application to wave directions in the Adriatic Sea is provided for illustration. | es_ES |
dc.description.sponsorship | The 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 (Grupos de Referencia Competitiva ED431C-2016-015, ED431C-2017-38 and ED431C-2020-14, and Centro de Investigación del SUG ED431G 2019/01), all of them through the ERDF. The authors thank Prof. Agnese Panzera, from the University of Florence, for her help in the theoretical developments of the paper and her general comments about this work. The authors also thank an Associate Editor and two anonymous referees for numerous useful comments that significantly improved this article. | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED481A-2017/361 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2016-015 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2017-38 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431C-2020-14 | es_ES |
dc.description.sponsorship | Xunta de Galicia; ED431G 2019/01 | es_ES |
dc.language.iso | eng | es_ES |
dc.relation | info: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 COMPLEJOS | es_ES |
dc.relation | info: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 DIMENSION | es_ES |
dc.relation.isversionof | https://doi.org/10.1007/s00477-020-01919-5 | |
dc.relation.uri | https://link.springer.com/article/10.1007/s00477-020-01919-5 | es_ES |
dc.rights | Todos os dereitos reservados. All rights reserved. | es_ES |
dc.subject | Angular risk | es_ES |
dc.subject | Circular data | es_ES |
dc.subject | Local polynomial regression | es_ES |
dc.subject | Spatial correlation | es_ES |
dc.subject | Wave orientation | es_ES |
dc.title | Nonparametric estimation of circular trend surfaces with application to wave directions | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
dc.identifier.doi | 10.1007/s00477-020-01919-5 |
Ficheiros no ítem
Este ítem aparece na(s) seguinte(s) colección(s)
-
GI-MODES - Artigos [137]