Variational Bayes for high-dimensional proportional hazards models with applications within gene expression

MOTIVATION: Few Bayesian methods for analyzing high-dimensional sparse survival data provide scalable variable selection, effect estimation and uncertainty quantification. Such methods often either sacrifice uncertainty quantification by computing maximum a posteriori estimates, or quantify the unce...

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Detalles Bibliográficos
Autores principales: Komodromos, Michael, Aboagye, Eric O, Evangelou, Marina, Filippi, Sarah, Ray, Kolyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364383/
https://www.ncbi.nlm.nih.gov/pubmed/35751586
http://dx.doi.org/10.1093/bioinformatics/btac416

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364383/
https://www.ncbi.nlm.nih.gov/pubmed/35751586
http://dx.doi.org/10.1093/bioinformatics/btac416

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