Bayesian survival analysis to model plant resistance and tolerance to virus diseases

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Abstract

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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Lázaro, E., Armero, C., & Rubio, L. (2017). Bayesian survival analysis to model plant resistance and tolerance to virus diseases. In Springer Proceedings in Mathematics and Statistics (Vol. 194, pp. 173–181). Springer New York LLC. https://doi.org/10.1007/978-3-319-54084-9_16

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