run.tfr.mcmc.extra: Run MCMC for Extra Countries, Areas or Regions
In jasonacollins/bayesTFR1: Bayesian Fertility Projection

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

Run MCMC for extra countries, areas or regions. It uses the posterior distribution of model hyperparameters from an existing simulation to generate country-specific parameters.

run.tfr.mcmc.extra(sim.dir = file.path(getwd(), "bayesTFR.output"), 
    countries = NULL, my.tfr.file = NULL, 
    iter = NULL, thin = 1, burnin = 2000,
    parallel = FALSE, nr.nodes = NULL,  my.locations.file = NULL,
    verbose = FALSE, verbose.iter = 100, ...)

`sim.dir`	Directory with an existing simulation.
`countries`	Vector of country codes. These include codes of areas and regions (see column `country_code` in `UNlocations`).
`my.tfr.file`	File name containing user-specified TFR time series for countries for which the simulation should run (see Details below).
`iter`	Number of iterations to be used for sampling from the posterior distribution of the hyperparameters. By default, the number of iterations used in the existing simulation is taken.
`thin`	Thinning interval for sampling from the posterior distribution of the hyperparameters.
`burnin`	Number of iterations discarded before sampling from the posterior distribution of the hyperparameters. It is also used when computing proposal of gamma covariance matrices (see `get.cov.gammas`).
`parallel`	Logical determining if the simulation should run multiple chains in parallel.
`nr.nodes`	Relevant only if `parallel` is `TRUE`. It gives the number of nodes for running the simulation in parallel. By default it equals to the number of chains contained in the existing simulation.
`my.locations.file`	File name containing user-specified locations. See Details below.
`verbose`	Logical switching log messages on and off.
`verbose.iter`	Integer determining how often (in number of iterations) log messages are outputted during the estimation.
`...`	Additional parameters to be passed to the function `performParallel`, if `parallel` is `TRUE`.

The function can be used to make predictions for countries, areas or regions (further denoted as ‘countries’) that were not included in the MCMC estimation (invoked by run.tfr.mcmc). It creates MCMC traces for country-specific parameters. The purpose of this function is to have country-specific parameters available in order to be able to generate projections for additional countries or their aggregations, without having to re-run the often time-expensive MCMC simulation.

The set of countries to be considered by this function can be given either by their codes, using the argument countries, in which case the countries must be included in the UN WPP tfr dataset. Or, it can be given by a user-specific TFR file, using the argument my.tfr.file. The function considers a union of both arguments. The function will ignore all countries that were used in the existing MCMC simulation for estimating the hyperparameters. Countries that already own country-specific parameters (e.g. because they were included in my.tfr.file passed to run.tfr.mcmc) get their parameters recomputed. Note that all countries should be included in the UNlocations dataset, but unlike in run.tfr.mcmc, their include_code is ignored. As in the case of run.tfr.mcmc, the default dataset of locations UNlocations can be overwritten using a file of the same structure as UNlocations passed via the my.locations.file argument. This file should be especially used, if TFR is simulated for new locations that are not included in UNlocations.

An object of class bayesTFR.mcmc.set.

If there is an existing projection for the directory sim.dir, use tfr.predict.extra to obtain projections for the extra countries used in this function.

Hana Sevcikova, Leontine Alkema

run.tfr.mcmc, tfr.predict.extra

## Not run: 
sim.dir <- tempfile()
m <- run.tfr.mcmc(nr.chains=1, iter=20, output.dir=sim.dir, verbose=TRUE)
m <- run.tfr.mcmc.extra(sim.dir=sim.dir, countries=c(908,924), burnin=10, verbose=TRUE)
summary(m, country=924)
pred <- tfr.predict(m, burnin=10, use.tfr3=FALSE, verbose=TRUE)
summary(pred, country=908)
unlink(sim.dir, recursive=TRUE)

## End(Not run)