# <markdowncell> # ### Plot the Results # <codecell> sim.run(0, 12) model.plot_distributions(show_normal=True) # <markdowncell> # ### Plot the joint distribution between parameters, $a$ and $K$ # <codecell> model.plot_joint_distribution('a', 'K', show_prior=False) # <markdowncell> # ...showing the joint, with the prior, to see how much the inference constrains the final best estimates of the parameters # <codecell> model.plot_joint_distribution('a', 'K', show_prior=True) # <markdowncell> # ### Sample Runs # <codecell>
# <markdowncell> # ### Plot the Results # <codecell> sim.run(0,12) model.plot_distributions(show_normal=True) # <markdowncell> # ### Plot the joint distribution between parameters, $a$ and $K$ # <codecell> model.plot_joint_distribution('a','K',show_prior=False) # <markdowncell> # ...showing the joint, with the prior, to see how much the inference constrains the final best estimates of the parameters # <codecell> model.plot_joint_distribution('a','K',show_prior=True) # <markdowncell> # ### Sample Runs # <codecell>