09. Bayesian Analysis, Plotting and MCMC Processor

Introduction

MCMC Processor is a class responsible for processing MCMC and producing validation plots etc.

Posteriors

It can produce posterior distribution with standard daignstoci

Bayes factor and Savage-Dickey

It is possible to obtain the Bayes factor for different hypothesis

  BayesFactor:
    # Goes as follows: ParamName Name[Model 1, Model 2], Model1[lower, upper ], Model2[lower, upper ]
    - ["sin2th_23", ["LO", "UO"], [0, 0.5], [0.5, 1]]

or calculate savage Dickey

  SavageDickey:
    - ["Alpha_q3", 0.0001, [0, 1]]

Credible Intervals

TODO!!!

2D

It is possible to produce 2D posteriors.

This can take some time though. There are two ways faster (using multithreading) but requiring lots of RAM or slower but without RAM requirements. Once you obtain 2D posteriors there are multiple additional plots you can produce.

Credible Region

TODO!!!

Triangle plot

TODO!!!

Violing plot

TODO!!!

BiPolar plot

TODO!!!

Parameter Evolution