e0.pardensity.plot: Plotting MCMC Parameter Density

Description

Functions for plotting density of the posterior distribution of the MCMC parameters.

Usage

e0.pardensity.plot(mcmc.list = NULL, 
    sim.dir = file.path(getwd(), "bayesLife.output"), 
    chain.ids = NULL, par.names = NULL, 
    burnin = NULL, dev.ncol = 5, low.memory = TRUE, ...)
    
e0.pardensity.cs.plot(country, mcmc.list = NULL, 
    sim.dir = file.path(getwd(), "bayesLife.output"), 
    chain.ids = NULL, par.names = NULL, 
    burnin = NULL, dev.ncol = 3, low.memory = TRUE, ...)

Arguments

country: Name or numerical code of a country.
mcmc.list: List of bayesLife.mcmc objects, or an object of class bayesLife.mcmc.set or of class bayesLife.prediction. If it is NULL, the parameter values are loaded from sim.dir.
sim.dir: Directory with the MCMC simulation results. It is only used if mcmc.list is NULL.
chain.ids: List of MCMC identifiers to be plotted. If it is NULL, all chains found in mcmc.list or sim.dir are plotted.
par.names: Names of parameters for which density should be plotted. By default all country-independent parameters are plotted if used within e0.pardensity.plot, or all country-specific parameters are plotted if used within e0.pardensity.cs.plot.
burnin: Number of iterations to be discarded from the beginning of each chain.
dev.ncol: Number of columns for the graphics device. If the number of parameters is smaller than dev.ncol, the number of columns is automatically decreased.
low.memory: Logical indicating if the processing should run in a memory-efficient mode.
...: Further arguments passed to the density function.

Author

Hana Sevcikova

Details

The functions plot the density of the posterior distribution either for country-independent parameters (e0.pardensity.plot) or for country-specific parameters (e0.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 bayesLife.prediction, thinned traces 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 e0.predict.

Examples

Run this code

sim.dir <- file.path(find.package("bayesLife"), "ex-data", "bayesLife.output")
e0.pardensity.plot(sim.dir = sim.dir, burnin = 10)
e0.pardensity.cs.plot(country = "Ireland", sim.dir = sim.dir, burnin = 10)