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
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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'))

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

On CRAN:

Conda-Forge:

2.70 score 139 downloads 1 exports 19 dependencies

Last updated 4 years agofrom:c174b470cd. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-winOKMar 05 2025
R-4.5-macOKMar 05 2025
R-4.5-linuxOKMar 05 2025
R-4.4-winOKMar 05 2025
R-4.4-macOKMar 05 2025
R-4.4-linuxOKMar 05 2025
R-4.3-winOKMar 05 2025
R-4.3-macOKMar 05 2025

Exports:mcmc

Dependencies:cliexpmfansigenericsgluelatticelifecyclemagrittrMASSMatrixmsmmvtnormpillarpkgconfigrlangsurvivaltibbleutf8vctrs