Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases

Viruses constitute a major threat to large-scale production of crops worldwide producing important economical losses and undermining sustainability. We evaluated a new plant variety for resistance and tolerance to a specific virus through a comparison with other well-known varieties. The study is ba...

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Autores principales: Lázaro, Elena, Armero, Carmen, Rubio, Luis
Otros Autores: Argiento, R.
Formato: article
Lenguaje:Inglés
Publicado: 2018
Acceso en línea:http://hdl.handle.net/20.500.11939/6058
https://link.springer.com/chapter/10.1007%2F978-3-319-54084-9_16
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author Lázaro, Elena
Armero, Carmen
Rubio, Luis
author2 Argiento, R.
author_browse Argiento, R.
Armero, Carmen
Lázaro, Elena
Rubio, Luis
author_facet Argiento, R.
Lázaro, Elena
Armero, Carmen
Rubio, Luis
author_sort Lázaro, Elena
collection ReDivia
description Viruses constitute a major threat to large-scale production of crops worldwide producing important economical losses and undermining sustainability. We evaluated a new plant variety for resistance and tolerance to a specific virus through a comparison with other well-known varieties. The study is based on two independent Bayesian accelerated failure time models which assess resistance and tolerance survival times. Information concerning plant genotype and virus biotype were considered as baseline covariates and error terms were assumed to follow a modified standard Gumbel distribution. Frequentist approach to these models was also considered in order to compare the results of the study from both statistical methodologies.
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spelling ReDivia60582025-04-25T14:46:04Z Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases Lázaro, Elena Armero, Carmen Rubio, Luis Argiento, R. Viruses constitute a major threat to large-scale production of crops worldwide producing important economical losses and undermining sustainability. We evaluated a new plant variety for resistance and tolerance to a specific virus through a comparison with other well-known varieties. The study is based on two independent Bayesian accelerated failure time models which assess resistance and tolerance survival times. Information concerning plant genotype and virus biotype were considered as baseline covariates and error terms were assumed to follow a modified standard Gumbel distribution. Frequentist approach to these models was also considered in order to compare the results of the study from both statistical methodologies. 2018-05-09T16:30:59Z 2018-05-09T16:30:59Z 2017 article Lázaro, E., Armero, C. & Rubio, L. (2017). Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases. In: Argiento R., Lanzarone E., Antoniano Villalobos I., Mattei A. (eds) Bayesian Statistics in Action. BAYSM 2016. Proceedings in Mathematics & Statistics, vol 194. 173-181. 2194-1009 http://hdl.handle.net/20.500.11939/6058 10.1007/978-3-319-54084-9_16 https://link.springer.com/chapter/10.1007%2F978-3-319-54084-9_16 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ electronico
spellingShingle Lázaro, Elena
Armero, Carmen
Rubio, Luis
Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title_full Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title_fullStr Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title_full_unstemmed Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title_short Bayesian Survival Analysis to Model Plant Resistance and Tolerance to Virus Diseases
title_sort bayesian survival analysis to model plant resistance and tolerance to virus diseases
url http://hdl.handle.net/20.500.11939/6058
https://link.springer.com/chapter/10.1007%2F978-3-319-54084-9_16
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