get_cov_gammas: Covariance Matrices of Gamma Parameters
In jasonacollins/bayesTFR1: Bayesian Fertility Projection

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

From a given MCMC, obtain a covariance matrix of the gamma_ci (i=1,2,3) parameters for each country c.

1	get.cov.gammas(mcmc.set = NULL, sim.dir = NULL, burnin = 200, chain.id = 1)

`mcmc.set`	Object of class `bayesTFR.mcmc.set`. If it is `NULL`, the `sim.dir` is used to load existing simulation results.
`sim.dir`	Directory with existing MCMC simulation results. It is only used if `mcmc.set` is `NULL`.
`burnin`	Number of burn-in iterations to be discarded from the begining of the chain.
`chain.id`	Identifier of the MCMC to be used. By default the first chain is used.

In order to speed-up MCMC convergence, the package contains default values of gamma covariance that were obtained from a previous run (they can be loaded using data(proposal_cov_gammas_cii)). However, this function allows to obtain new values and overwrite the default values by passing the resulting object to the run.tfr.mcmc function as the proposal_cov_gammas argument.

A list with components:

`values`	An array of size nr_countries x 3 x 3 containing values of the covariance matrix of gamma_ci (i=1,2,3) for each country c.
`country_codes`	A vector of size nr_countries. A covariance matrix `values[i,,]` corresponds to a country with the code `country_codes[i]`.

Leontine Alkema, Hana Sevcikova

run.tfr.mcmc

## Not run: 
sim.dir <- file.path(find.package("bayesTFR"), "ex-data", "bayesTFR.output")
cov.gammas <- get.cov.gammas(sim.dir=sim.dir, burnin=0)
m <- run.tfr.mcmc(nr.chains=1, iter=10, proposal_cov_gammas=cov.gammas, verbose=TRUE)

## End(Not run)