Plotting Bayesian Analysis#

A number of function exist for plotting the results of Bayesian analysis.

Reflectivity and SLD#

A simple reflectivity shaded plot can be displayed as follows:

figure(1); clf;
bayesShadedPlot(problem,results)
simple shaded plot

By default, this shows a standard reflectivity plot with a 65% shaded confidence interval.

There are a number of options to customise the plot:

Interval - You can sepcify either the 65% or 95% confidence interval to display:

bayesShadedPlot(problem,results,'interval',95)
95 shaded plot

Type - You can also specify a q4 plot for the reflectivity:

bayes q4 plot

Posterior Histograms#

You can easily view the marginalised Bayesian posteriors from your analysis:

plotHists(results)
smooth hists

By default, plotHists carries out a KDE smooth of the histograms. You can optionally choose no smoothing:

plotHists(results,'smooth',false)
smooth hists

Corner Plots#

To produce a cornerplot, simply use the cornerPlot function:

cornerPlot(results)
cornerPlot

Chain View#

Finally, you can check the integrity of your markov chain as follows:

mcmcplot(results.chain,[],results.fitNames,'chainpanel');
chainPlot