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BayesSurvive  

Bayesian Survival Models for High-Dimensional Data
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]
All associated links for this package
First Published: 2024-04-23
Latest Update: 2025-03-25
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 17 Jul. 2026.
Previous versions and publish date:
0.0.1 (2024-04-23 13:20), 0.0.2 (2024-06-04 15:20), (2026-07-09 07:58)
Other packages that cited BayesSurvive R package
View BayesSurvive citation profile
Other R packages that BayesSurvive depends, imports, suggests or enhances
Complete documentation for BayesSurvive
Functions, R codes and Examples using the BayesSurvive R package
Full BayesSurvive package functions and examples
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