summary.bayesMig.mcmc: Summary Statistics for Migration Markov Chain Monte Carlo

Description

Summary of an object bayesMig.mcmc.set or bayesMig.mcmc, computed via run.mig.mcmc. It can be obtained either for all locations or for a specific location, and either for all parameters or for specific parameters. The function uses the summary.mcmc function of the coda package.

Usage

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

Value

Return list with elements:

meta: contains meta information about the object.
results: contains result of summary.mcmc.
country.name: optional; available if country is provided as argument.

Arguments

object: Object of class bayesMig.mcmc.set or bayesMig.mcmc.
country: Location name or code if a location-specific summary is desired. The code can be either numeric or (if locations are countries) ISO-2 or ISO-3 characters. By default, summary for all locations is generated.
par.names: Country independent parameters (hyperparameters) to be included in the summary. The default names are given by mig.parameter.names().
par.names.cs: Location-specific parameters to be included in the summary. The default names are given by mig.parameter.names.cs().
thin: Thinning interval. Only used if larger than the thin argument used in run.mig.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.
chain.id: Identifiers of MCMC chains. By default, all chains are considered.
meta.only: Logical. If it is TRUE, only meta information of the simulation is included.

Examples

Run this code

# See example in ?run.mig.mcmc

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