Bayesian Survival Models for High-Dimensional Data R package BayesSurvive version 0.1.0 CRAN Task View: Survival (https://CRAN.R-project.org/view=Survival) 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 (Hermansen et al., 2025 <doi:10.48550/arXiv.2503.13078>). Software Depends: R (>= 4.1.0) Imports: Rcpp, ggplot2, GGally, mvtnorm, survival, riskRegression, utils, stats, methods LinkingTo: Rcpp, RcppArmadillo, testthat Suggests: knitr, testthat, Matrix Zhi Zhao <zhi.zhao@medisin.uio.no> Comprehensive R Archive Network (CRAN) Zhi Zhao [aut, cre], Waldir Leoncio [aut], Katrin Madjar [aut], Tobias Østmo Hermansen [aut], Manuela Zucknick [ctb], Jörg Rahnenführer [ctb] GPL-3 2025-03-25 application/tgz https://CRAN.R-project.org/package=BayesSurvive doi:10.32614/CRAN.package.BayesSurvive