mig.pardensity.plot {bayesMig}R Documentation

Plotting MCMC Parameter Density


Functions for plotting the density of the posterior distribution of the MCMC parameters from the migration model.


  mcmc.list = NULL,
  sim.dir = NULL,
  chain.ids = NULL,
  par.names = mig.parameter.names(),
  burnin = NULL,
  dev.ncol = 2,
  low.memory = TRUE,

  mcmc.list = NULL,
  sim.dir = NULL,
  chain.ids = NULL,
  par.names = mig.parameter.names.cs(),
  burnin = NULL,
  dev.ncol = 3,
  low.memory = TRUE,



List of bayesMig.mcmc objects, or an object of class bayesMig.mcmc.set or of class bayesMig.prediction. If it is NULL, the values are loaded from sim.dir.


Directory with the MCMC simulation results. It is only used if mcmc.list is NULL.


List of MCMC identifiers to be plotted. If it is NULL, all chains found in mcmc.list or sim.dir are plotted.


Names of parameters for which density should be plotted. By default all country-independent parameters are plotted if used within mig.pardensity.plot, or country-specific parameters are plotted if used within mig.pardensity.cs.plot.


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


Number of column for the graphics device. If the number of parameters is smaller than dev.ncol, the number of columns is automatically decreased.


Logical indicating if the processing should run in a low-memory mode. If it is FALSE, traces of all available parameters are loaded into memory. Otherwise, parameters are loaded as they are needed.


Further arguments passed to the density function.


Name or numerical code of a country. It can also be given as ISO-2 or ISO-3 characters.


The functions plot the density of the posterior distribution either for country-independent parameters (mig.pardensity.plot or for country-specific parameters (mig.pardensity.cs.plot, one graph per parameter. One can restrict it to specific chains by setting the chain.ids argument and to specific parameters by setting the par.names argument.

If mcmc.list is an object of class bayesMig.prediction and if this object contains thinned traces, they are used instead of the full chains. In such a case, burnin and chain.ids cannot be modified - their value is set to the one used when the thinned traces were created, namely when running mig.predict. In a situation with long MCMC chains, this approach can significantly speed-up creation of the density plots.


No return value.

[Package bayesMig version 0.4-6 Index]