This package is considered a duplicate. The official version of this package is found at:https://ocbe-uio.r-universe.dev/BayesSurvive

Package: BayesSurvive 0.0.2

Zhi Zhao

BayesSurvive: Bayesian Survival Models for High-Dimensional Data

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.

Authors:Zhi Zhao [aut, cre], Katrin Madjar [aut], Tobias Østmo Hermansen [aut], Manuela Zucknick [ctb], Jörg Rahnenführer [ctb]

BayesSurvive_0.0.2.tar.gz
BayesSurvive_0.0.2.tar.gz(r-4.5-noble)BayesSurvive_0.0.2.tar.gz(r-4.4-noble)
BayesSurvive_0.0.2.tgz(r-4.4-emscripten)
BayesSurvive.pdf |BayesSurvive.html✨
BayesSurvive/json (API)
NEWS

# Install 'BayesSurvive' in R:

install.packages('BayesSurvive', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ocbe-uio/bayessurvive/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

simData - Simulated survival data

openblas cpp openmp

3.00 score 1 scripts 223 downloads 7 exports 118 dependencies

Last updated 7 months agofrom:4c24b33005. Checks:OK: 2. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Dec 02 2024
R-4.5-linux-x86_64	OK	Dec 02 2024

Exports:BayesSurvive func_MCMC func_MCMC_graph plotBrier UpdateGamma UpdateRPlee11 VS

Dependencies:backports base64enc bslib cachem checkmate cli cluster cmprsk codetools colorspace cpp11 crayon data.table diagram digest doParallel dplyr evaluate fansi farver fastmap fontawesome forcats foreach foreign Formula fs future future.apply generics GGally ggplot2 ggstats globals glue gridExtra gtable highr Hmisc hms htmlTable htmltools htmlwidgets isoband iterators jquerylib jsonlite KernSmooth knitr labeling lattice lava lifecycle listenv magrittr MASS Matrix MatrixModels memoise mets mgcv mime multcomp munsell mvtnorm nlme nnet numDeriv parallelly patchwork pillar pkgconfig plotrix plyr polspline prettyunits prodlim progress progressr Publish purrr quantreg R6 ranger rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen riskRegression rlang rmarkdown rms rpart rstudioapi sandwich sass scales shape SparseM SQUAREM stringi stringr survival TH.data tibble tidyr tidyselect timereg tinytex utf8 vctrs viridis viridisLite withr xfun yaml zoo

Bayesian Cox Models with graph-structure priors

Rendered fromBayesCox.Rmdusingknitr::rmarkdownon Dec 02 2024.

Last update: 2024-06-05
Started: 2024-06-05

Help page	Topics
Fit Bayesian Cox Models	BayesSurvive
Create a dataframe of estimated coefficients	coef.BayesSurvive
Function to run MCMC sampling	func_MCMC
Function to learn MRF graph	func_MCMC_graph
Create a plot of estimated coefficients	plot.BayesSurvive
Time-dependent Brier scores	plotBrier
Predict survival risk	predict.BayesSurvive
Simulated survival data	simData
Subfunctions to update parameters	UpdateGamma
Update coefficients of Bayesian Cox Models	UpdateRPlee11
Function to perform variable selection	VS

Package: BayesSurvive 0.0.2

BayesSurvive: Bayesian Survival Models for High-Dimensional Data

Bayesian Cox Models with graph-structure priors

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)