In runMCMCbtadjust: Runs Monte Carlo Markov Chain - With Either 'JAGS', 'nimble' or 'greta' - While Adjusting Burn-in and Thinning Parameters

Parallelization

The function runMCMC_btadjust() now allows automatic parallelization of different Markov chains of the MCMC parts of the algorithm which can be of interest when we have several Markov chains. When the user wishes to use parallelization, the only difference with the preceding calls are the addition of control.MCMC=list(parallelize=TRUE) - or of parallelize=TRUE in control.MCMC if already present. Here are examples below, with 2 chains only (a condition required by CRAN to accept parallelization in vignettes).

library(parallel)

### put here to pass CRAN tests: https://stackoverflow.com/questions/41307178/error-processing-vignette-failed-with-diagnostics-4-simultaneous-processes-spa
options(mc.cores=2)

### adapted the number of chains for the same reason
Nchains.parallel<-2

out.mcmc.Nimble.parallel<-runMCMC_btadjust(code=ModelCode, constants = ModelConsts, data = ModelData, MCMC_language="Nimble",
    Nchains=Nchains.parallel, params=params, inits=Inits[1:Nchains.parallel],
    niter.min=1000, niter.max=300000,
    nburnin.min=100, nburnin.max=200000, 
    thin.min=1, thin.max=1000,
    conv.max=1.05, neff.min=1000,
    control.MCMC=list(parallelize=TRUE))

out.mcmc.Jags.parallel<-runMCMC_btadjust(code=modeltotransfer,  data = ModelData.Jags, MCMC_language="Jags", 
    Nchains=Nchains.parallel, params=params, inits=Inits[1:Nchains.parallel],
    niter.min=1000,niter.max=300000,
    nburnin.min=100,nburnin.max=200000,
    thin.min=1,thin.max=1000,
        conv.max=1.05,neff.min=1000,
    control.MCMC=list(parallelize=TRUE))

runMCMCbtadjust documentation built on June 22, 2024, 10:24 a.m.