Convergence Diagnostics

Convergence diagnostics are methods used to determine if a statistical simulation, like Markov Chain Monte Carlo (MCMC), has run long enough to reliably estimate a model's parameters. Think of it as checking whether a process has settled into a stable pattern and is no longer changing significantly. If the process converges, the results are trustworthy and representative of the true distribution. These diagnostics help researchers decide when to stop the simulation, ensuring efficient use of resources and accurate conclusions.