bayesTFR (version 4.2-0)

run.tfr3.mcmc: Running Markov Chain Monte Carlo for Parameters of Total Fertility Rate in Phase III

Description

Runs (or continues running) MCMCs for simulating phase III total fertility rate, using a Bayesian hierarchical version of an AR(1) model.

Usage

run.tfr3.mcmc(sim.dir, nr.chains = 3, iter = 50000, thin = 10, 
    replace.output = FALSE, my.tfr.file = NULL, buffer.size = 100, 
    use.extra.countries = FALSE, 
    mu.prior.range = c(0, 2.1), rho.prior.range = c(0, 1 - .Machine$double.xmin), 
    sigma.mu.prior.range = c(1e-05, 0.318), sigma.rho.prior.range = c(1e-05, 0.289), 
    sigma.eps.prior.range = c(1e-05, 0.5), 
    mu.ini = NULL, mu.ini.range = mu.prior.range, 
    rho.ini = NULL, rho.ini.range = rho.prior.range, 
    sigma.mu.ini = NULL, sigma.mu.ini.range = sigma.mu.prior.range, 
    sigma.rho.ini = NULL, sigma.rho.ini.range = sigma.rho.prior.range, 
    sigma.eps.ini = NULL, sigma.eps.ini.range = sigma.eps.prior.range, 
    seed = NULL, parallel = FALSE, nr.nodes = nr.chains, compression.type = "None", 
    auto.conf = list(max.loops = 5, iter = 50000, iter.incr = 20000, nr.chains = 3, 
                    thin = 60, burnin = 10000), 
    verbose = FALSE, verbose.iter = 1000, ...)
        
continue.tfr3.mcmc(sim.dir, iter, chain.ids=NULL, 
    parallel = FALSE, nr.nodes = NULL, auto.conf = NULL,
    verbose=FALSE, verbose.iter = 1000, ...)

Value

An object of class bayesTFR.mcmc.set which is a list with two components:metaAn object of class bayesTFR.mcmc.meta.mcmc.listA list of objects of class bayesTFR.mcmc, one for each MCMC.

Details

The MCMCs are stored in sim.dir in a subdirectory called phaseIII. It has exactly the same structure as phase II MCMCs described in run.tfr.mcmc.

References

Raftery, A.E., Alkema, L. and Gerland, P. (2014). http://www.ncbi.nlm.nih.gov/pubmed/25324591{Bayesian Population Projections for the United Nations.} Statistical Science, Vol. 29, 58-68.

See Also

run.tfr.mcmc, get.tfr3.mcmc

Examples

sim.dir <- tempfile()
# Runs Phase II MCMCs (must be run before Phase III)
m <- run.tfr.mcmc(nr.chains=1, iter=5, output.dir=sim.dir, verbose=TRUE)
# Runs Phase III MCMCs
m3 <- run.tfr3.mcmc(sim.dir=sim.dir, nr.chains=2, iter=50, thin=1, verbose=TRUE)
m3 <- continue.tfr3.mcmc(sim.dir=sim.dir, iter=10, verbose=TRUE)
summary(m3, burnin=10)
unlink(sim.dir, recursive=TRUE)