get.cov.gammas | R Documentation |
From a given MCMC, obtain a covariance matrix of the \gamma_{ci}
(i=1,2,3
) parameters for each country c
.
get.cov.gammas(mcmc.set = NULL, sim.dir = NULL, burnin = 200, chain.id = 1)
mcmc.set |
Object of class |
sim.dir |
Directory with existing MCMC simulation results. It is only used if |
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 |
country_codes |
A vector of size nr_countries. A covariance matrix |
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)
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