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BayesSurvive
View on CRAN: Click
here
Download and install BayesSurvive package within the R console
Install from CRAN:
install.packages("BayesSurvive")
Install from Github:
library("remotes")
install_github("cran/BayesSurvive")
Install by package version:
library("remotes")
install_version("BayesSurvive", "0.1.0")
Attach the package and use:
library("BayesSurvive")
Maintained by
Zhi Zhao
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.BayesSurvive . https://github.com/ocbe-uio/BayesSurvive/issues . https://github.com/ocbe-uio/BayesSurvive . BayesSurvive citation info . BayesSurvive results . BayesSurvive.pdf . BayesSurvive_0.1.0.tar.gz . BayesSurvive_0.1.0.zip . BayesSurvive_0.1.0.zip . BayesSurvive_0.1.0.zip . BayesSurvive_0.1.0.tgz . BayesSurvive_0.1.0.tgz . BayesSurvive_0.1.0.tgz . BayesSurvive_0.1.0.tgz . BayesSurvive archive . https://CRAN.R-project.org/package=BayesSurvive .
First Published: 2024-04-23
Latest Update: 2024-04-23
Description:
An implementation of Bayesian survival models with graph-structured selection priors for sparse identification of omics features predictive of survival (Madjar et al., 2021 <doi:10.1186/s12859-021-04483-z>) and its extension to use a fixed graph via a Markov Random Field (MRF) prior for capturing known structure of omics features, e.g. disease-specific pathways from the Kyoto Encyclopedia of Genes and Genomes database.
How to cite:
Zhi Zhao (2024). BayesSurvive: Bayesian Survival Models for High-Dimensional Data. R package version 0.1.0, https://cran.r-project.org/web/packages/BayesSurvive. Accessed 03 May. 2025.
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