Bayesian Credible Interval Tranche Triggers in Capital Escrow Structures
Escrow capital releases bound to Bayesian credible interval lower limits prevent premature tranche disbursements during volatile commissioning ramp phases.
Prior Distribution
Meaning
Statistical representation of the information or beliefs about a parameter that exist before any new data from a current study is considered. A prior distribution sets the baseline for bayesian inference by incorporating historical data, expert opinion or physical laws into the model. It defines the starting point for the update process that leads to a posterior estimate.
Choosing an appropriate starting range is a critical step in the design of a bayesian experiment.
Information Source
Input for this function can come from previous production runs, similar facilities or fundamental scientific principles. A well-sourced baseline improves the accuracy of the final model, especially when new data is limited.
Subjective Weight
Influence of this starting belief on the final result depends on how much new evidence is collected. If the new data is very strong, it will overwhelm the initial assumption.
Inference Baseline
Specification of the range can be broad to represent high uncertainty or narrow to represent high confidence. This choice affects how quickly the model adapts to new information from the plant. Failure to state these assumptions clearly leads to biased results in the final audit.
The distribution must be defensible based on demonstrated rates from earlier trials.