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Posterior inference

graph LR
    g0[Project loading];
    g1[Prior elicitation];
    g2[Posterior inference];
    g3[Post-MCMC analysis];
    g0 --> g1;
    g1 --> g2;
    g2 --> g3;

    classDef selected-mermaid-node fill:#33658a60,stroke:#cc5f00,stroke-width:4px
    class g2 selected-mermaid-node

After prior elicitation, when the chronological DAG has been produced for a model, users can compute joint posterior estimates for all parameters in the model following a MCMC algorithm.

MCMC calibration

Posterior densities for the current model can be generated by selecting Tools > Calibrate model on the stratigraphy and supplementary data tab.

This will initiate the MCMC algorithm with a popup window showing progress of the MCMC calibration, as shown below. Calibration may take a while to complete for larger and more complex models.

MCMC Calibration will run until a minimum number of accepted samples (50000) is achieved.

A screenshot of the MCMC progress bar popup

Batch MCMC calibration

If you have multiple models within a project, a batch of models can be calibrated by selecting Tools > Calibrate multiple models from project and selecting models to calibrate.

Only models which have been saved after completing prior elicitation (i.e. models with chronological graphs) can be selected for batch calibration.

Calibrations are currently executed in sequence, but fewer accepted MCMC samples are required than for individual model sampling.

Next

Once you have calibrated your model(s), proceed to post-MCMC analysis.