summary.bayesTFR.mcmc.set {bayesTFR}

Summary Statistics for TFR Markov Chain Monte Carlo Chains

Description

Summary of an object bayesTFR.mcmc.set or bayesTFR.mcmc, computed via run.tfr.mcmc or run.tfr3.mcmc. It can be obtained either for all countries or for a specific country, and either for all parameters or for specific parameters. The function uses the summary.mcmc function of the coda package.

Usage

## S3 method for class 'bayesTFR.mcmc.set'
summary(object, country = NULL, chain.id = NULL,
    par.names = NULL, par.names.cs = NULL, meta.only = FALSE, 
    thin = 1, burnin = 0, ...)
	
## S3 method for class 'bayesTFR.mcmc'
summary(object, country = NULL, par.names = NULL, par.names.cs = NULL, 
    thin = 1, burnin = 0, ...)

Arguments

object

Object of class bayesTFR.mcmc.set or bayesTFR.mcmc.

country

Country name or code if a country-specific summary is desired. The code can be either numeric or ISO-2 or ISO-3 characters. By default, summary for all countries is generated.

chain.id

Identifiers of MCMC chains. By default, all chains are considered.

par.names

Country independent parameters to be included in the summary. If the underlying object is an MCMC of phase II, the default names are given by tfr.parameter.names(), if it is phase III the names are tfr3.parameter.names().

par.names.cs

Country-specific parameters to be included in the summary. If the underlying object is an MCMC of phase II, the default names are given by tfr.parameter.names.cs(), if it is phase III the names are tfr3.parameter.names.cs().

meta.only

If it is TRUE, only meta information of the simulation is included.

thin

Thinning interval. Only used if larger than the thin argument used in run.tfr.mcmc or run.tfr3.mcmc.

burnin

Number of iterations to be discarded from the beginning of each chain before computing the summary.

...

Additional arguments passed to the summary.mcmc function of the coda package.

Author(s)

Hana Sevcikova

See Also

bayesTFR.mcmc.set, summary.mcmc

Examples

sim.dir <- file.path(find.package("bayesTFR"), "ex-data", "bayesTFR.output")
m <- get.tfr.mcmc(sim.dir)
summary(m, country="CZE", burnin=15)