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>).
Version: 0.1.0 Depends: R (≥ 4.1.0) Imports: Rcpp, ggplot2, GGally, mvtnorm, survival, riskRegression, utils, stats, methods LinkingTo: Rcpp, RcppArmadillo, testthat Suggests: knitr, testthat, Matrix Published: 2025-03-25 DOI: 10.32614/CRAN.package.BayesSurvive Author: Zhi Zhao [aut, cre], Waldir Leoncio [aut], Katrin Madjar [aut], Tobias Ãstmo Hermansen [aut], Manuela Zucknick [ctb], Jörg Rahnenführer [ctb] Maintainer: Zhi Zhao <zhi.zhao at medisin.uio.no> BugReports: https://github.com/ocbe-uio/BayesSurvive/issues License: GPL-3 URL: https://github.com/ocbe-uio/BayesSurvive NeedsCompilation: yes Citation: BayesSurvive citation info Materials: README NEWS In views: Survival CRAN checks: BayesSurvive results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=BayesSurvive to link to this page.
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