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Comments on: Nonparametric estimation in mixture cure models with covariates
dc.contributor.author | Cao, Ricardo | |
dc.date.accessioned | 2023-10-13T10:50:02Z | |
dc.date.available | 2023-10-13T10:50:02Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | R. Cao, "Comments on: Nonparametric estimation in mixture cure models with covariates", TEST 32, pp. 499–505, 2023. https://doi.org/10.1007/s11749-023-00856-z | es_ES |
dc.identifier.uri | http://hdl.handle.net/2183/33762 | |
dc.description | Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG | es_ES |
dc.description | Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. | es_ES |
dc.description.abstract | [Abstract]: This paper discusses the invited paper by López-Cheda, Peng and Jácome on nonparametric mixture cure models with covariates. An alternative estimation procedure is proposed in this context. The situation when the two covariate vectors (the one in the incidence and in the latency parts) share some, but not all, their covariates is also considered. Some technical aspects in the assumptions, results and proofs of the invited paper are also discussed. Comments on the simulations and the real-data application are included. Finally, possible interesting topics for further research in this field are briefly discussed. | es_ES |
dc.description.sponsorship | This research has been supported by MICINN Grant PID2020-113578RBI00 and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema Universitario de Galicia ED431G 2019/01), all of them through the European Regional Development Fund (ERDF). Funding for open access charge: Universidade da Coruña/CISUG. | 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.publisher | Springer Science and Business Media Deutschland GmbH | es_ES |
dc.relation | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113578RB-I00/ES/MÉTODOS ESTADÍSTICOS FLEXIBLES EN CIENCIA DE DATOS PARA DATOS COMPLEJOS Y DE GRAN VOLUMEN: TEORÍA Y APLICACIONES | es_ES |
dc.relation.uri | https://doi.org/10.1007/s11749-023-00856-z | es_ES |
dc.rights | Atribución 4.0 Internacional CC BY 4.0 | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | Censored data | es_ES |
dc.subject | Cure models | es_ES |
dc.subject | Nonparametric estimation | es_ES |
dc.title | Comments on: Nonparametric estimation in mixture cure models with covariates | es_ES |
dc.type | info:eu-repo/semantics/annotation | es_ES |
dc.rights.access | info:eu-repo/semantics/openAccess | es_ES |
UDC.journalTitle | TEST | es_ES |
UDC.volume | 32 | es_ES |
UDC.startPage | 499 | es_ES |
UDC.endPage | 505 | es_ES |
dc.identifier.doi | 10.1007/s11749-023-00856-z |
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