Burke–Fisher method

The Burke–Fisher method is a technique used in Bayesian statistics to efficiently update beliefs as new data arrives. Instead of recalculating everything from scratch each time, it adds new information to previous results in a step-by-step way. Think of it like updating a running total: after reviewing each new piece of evidence, you adjust your probability estimate accordingly. This approach makes analyzing large or complex data more manageable by breaking down the process into smaller, incremental steps, ensuring that your updated beliefs stay accurate and computationally feasible.