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_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)
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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'))

Peer review:

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

On CRAN:

2.70 score 116 downloads 1 exports 19 dependencies

Last updated 4 years agofrom:c174b470cd. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winOKNov 05 2024
R-4.5-linuxOKNov 05 2024
R-4.4-winOKNov 05 2024
R-4.4-macOKNov 05 2024
R-4.3-winOKNov 05 2024
R-4.3-macOKNov 05 2024

Exports:mcmc

Dependencies:cliexpmfansigenericsgluelatticelifecyclemagrittrMASSMatrixmsmmvtnormpillarpkgconfigrlangsurvivaltibbleutf8vctrs