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)

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)

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

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

plotHists(results)

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

plotHists(results,'smooth',false)

To produce a cornerplot, simply use the cornerPlot function:

cornerPlot(results)

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

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