plot_MCMC  R Documentation 
This function uses the output of rjags::jags.model to visualise the traces of the MCMC and the
corresponding densities. In particular it displays the posterior distributions of the age, if it is calculated,
palaeodose and the equivalent dose dispersion parameters of the sample. The function output is very
similar to plot output produced with the 'coda' package, but tailored to meet the needs in
the context of the 'BayLum'
package.
plot_MCMC( object, sample_names = NULL, variables = c("A", "D", "sD"), axes_labels = c(A = "Age (ka)", D = "D (Gy)", sD = "sD (Gy)"), n.chains = NULL, n.iter = 1000, smooth = FALSE, rug = TRUE, plot_single = FALSE, ... )
object 
coda::mcmc.list or coda::mcmc (required): Output generated by rjags::jags.model, e.g., in Age_Computation 
sample_names 
character (optional): Names of the used samples. This argument overrides the optional
argument 
variables 
character (with default): Variables in your coda::mcmc object to be plotted. 
axes_labels 
character (with default): Axes labels used for the trace and density plots. The labels should be provided as named character vector with the parameter names as the names used to assign the axes labelling. The labelling for the xaxis (trace plots) and yaxis (density plot) cannot be modified. 
n.chains 
numeric (optional): Set the number of chains to visualise, if nothing is provided the number of chains is determined from the input object 
n.iter 
integer (with default): Set the number of iterations to be visualised in the trace plots, regardless
of the size of the input dataset as long as the real number of iterations is > 
smooth 
logical (with default): Enable/disables smooth of trace plots using stats::smooth 
rug 
logical (with default): Enable/disables rug under density plots 
plot_single 
logical (with default): Enables/disables the single plot mode of the function, i.e.
if set to 
... 
further arguments that can be passed to modify the plot output. Supported arguments are

The function is used in the function Age_Computation, AgeS_Computation and Palaeodose_Computation, but can be used also as standalone plot function.
Two plots: Traces of the MCMC chains and the corresponding density plots. This plots are similar to coda::traceplot and coda::densplot.
0.1.4
Kreutzer, S., Christophe, C., 2022. plot_MCMC(): Plot MCMC trajectories and posterior distributions. Function version 0.1.4. In: Christophe, C., Philippe, A., Kreutzer, S., Guerin, G., 2022. BayLum: Chronological Bayesian Models Integrating Optically Stimulated. R package version 0.2.1. https://CRAN.rproject.org/package=BayLum
Sebastian Kreutzer, Geography & Earth Sciences, Aberystwyth University (United Kingdom). This function is a rewritten version of the function 'MCMC_plot()' by Claire Christophe
Age_Computation, AgeS_Computation, Palaeodose_Computation, rjags::coda.samples and rjags packages.
data(MCMCsample,envir = environment()) object < coda::as.mcmc(MCMCsample) plot_MCMC(object)
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