get.thinned.tfr.mcmc: Creating and Accessing Thinned MCMCs
In jasonacollins/bayesTFR1: Bayesian Fertility Projection

Description Usage Arguments Details Value Author(s) See Also Examples

The function get.thinned.tfr.mcmc accesses a thinned and burned version of the given Phase II MCMC set. create.thinned.tfr.mcmc creates such a set.

get.thinned.tfr.mcmc(mcmc.set, thin = 1, burnin = 0)

create.thinned.tfr.mcmc(mcmc.set, thin = 1, burnin = 0, 
    output.dir = NULL, verbose = TRUE)

`mcmc.set`	Object of class `bayesTFR.mcmc.set` of Phase II.
`thin, burnin`	Thinning interval and burnin used for creating or identifying the thinned object.
`output.dir`	Output directory. It is only used if the output goes to a non-standard directory.
`verbose`	Logical switching log messages on and off.

The function create.thinned.tfr.mcmc is called from tfr.predict and thus, the resulting object contains exactly the same MCMCs used for generating projections. In addition, it can be also called from tfr.diagnose if desired, so that the projection process can re-use such a set that lead to a convergence.

The thinning is done as follows: The given burnin is removed from the beginning of each chain in the original MCMC set. Then each chain is thinned by thin using equal spacing and all chains are collapsed into one single chain per parameter. They are stored in the main simulation directory under the name ‘thinned_mcmc_t_b’ where t is the value of thin and b the value of burnin.

Both functions return an object of class bayesTFR.mcmc.set. get.thinned.tfr.mcmc returns NULL if such object does not exist.

Hana Sevcikova

bayesTFR.mcmc.set, tfr.predict, tfr.diagnose

## Not run: 
sim.dir <- tempfile()
m <- run.tfr.mcmc(nr.chains=2, iter=30, seed=1, output.dir=sim.dir, verbose=TRUE)
tfr.predict(m, burnin=15, use.tfr3=FALSE) # creates thinned MCMCs
mb <- get.thinned.tfr.mcmc(m, thin=1, burnin=15)
summary(mb, meta.only=TRUE) # length 30 = 2chains x (30-15)iters.
unlink(sim.dir, recursive=TRUE)

## End(Not run)