Package: SurviMChd 0.1.2

SurviMChd: High Dimensional Survival Data Analysis with Markov Chain Monte Carlo

High dimensional survival data analysis with Markov Chain Monte Carlo(MCMC). Currently supports frailty data analysis. Allows for Weibull and Exponential distribution. Includes function for interval censored data.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Akash Pawar [aut, ctb]

SurviMChd_0.1.2.tar.gz
SurviMChd_0.1.2.zip(r-4.7-any)SurviMChd_0.1.2.zip(r-4.6-any)SurviMChd_0.1.2.zip(r-4.5-any)
SurviMChd_0.1.2.tgz(r-4.6-any)SurviMChd_0.1.2.tgz(r-4.5-any)
SurviMChd_0.1.2.tar.gz(r-4.7-any)SurviMChd_0.1.2.tar.gz(r-4.6-any)
SurviMChd_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SurviMChd/json (API)

# Install 'SurviMChd' in R:
install.packages('SurviMChd', repos = c('https://atanubhattacharjee.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • frailty - Frailty in high dimensional survival data.
  • headnneck - High dimensional genomic data on head and neck cancer
  • hnscc - Hnscc Head and neck cancer data
  • mcsurv - Metronomic cancer data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

jagscpp

1.00 score 279 downloads 7 exports 24 dependencies

Last updated from:52866a4d38. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK107
source / vignettesOK150
linux-releaseOK117
macos-releaseOK128
macos-oldrelOK85
windows-develOK96
windows-releaseOK71
windows-oldrelOK86
wasm-releaseOK99

Exports:fraidmfraidpmfrairandsurvexpMCsurvMCsurvMCmultisurvweibMC

Dependencies:abindbootclicodadplyrgenericsgluelatticelifecyclemagrittrpillarpkgconfigR2jagsR2WinBUGSR6rjagsrlangstringistringrtibbletidyselectutf8vctrswithr