Package: semmcmc 0.0.6

semmcmc: Bayesian Structural Equation Modeling in Multiple Omics Data Integration

Provides Markov Chain Monte Carlo (MCMC) routine for the structural equation modelling described in Maity et. al. (2020) <doi:10.1093/bioinformatics/btaa286>. This MCMC sampler is useful when one attempts to perform an integrative survival analysis for multiple platforms of the Omics data where the response is time to event and the predictors are different omics expressions for different platforms.

Authors:Arnab Maity [aut, cre], Sang Chan Lee [aut], Bani K. Mallick [aut], Samsiddhi Bhattacharjee [aut], Nidhan K. Biswas [aut]

semmcmc_0.0.6.tar.gz
semmcmc_0.0.6.zip(r-4.5)semmcmc_0.0.6.zip(r-4.4)semmcmc_0.0.6.zip(r-4.3)
semmcmc_0.0.6.tgz(r-4.4-any)semmcmc_0.0.6.tgz(r-4.3-any)
semmcmc_0.0.6.tar.gz(r-4.5-noble)semmcmc_0.0.6.tar.gz(r-4.4-noble)
semmcmc_0.0.6.tgz(r-4.4-emscripten)semmcmc_0.0.6.tgz(r-4.3-emscripten)
semmcmc.pdf |semmcmc.html
semmcmc/json (API)

# Install 'semmcmc' in R:
install.packages('semmcmc', repos = c('https://maitya02.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/maitya02/semmcmc/issues

On CRAN:

1 exports 0.62 score 7 dependencies 133 downloads

Last updated 3 years agofrom:c174b470cd. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 06 2024
R-4.5-winOKSep 06 2024
R-4.5-linuxOKSep 06 2024
R-4.4-winOKSep 06 2024
R-4.4-macOKSep 06 2024
R-4.3-winOKSep 06 2024
R-4.3-macOKSep 06 2024

Exports:mcmc

Dependencies:expmlatticeMASSMatrixmsmmvtnormsurvival