Convergence diagnostics refers to the set of techniques used to determine whether a statistical model has reached a stable solution during the estimation process, particularly in Bayesian analysis. These techniques assess whether the sampling algorithms have converged to the target posterior distribution, ensuring that the results obtained from the model are reliable and valid. Understanding convergence diagnostics is crucial in Bayesian probability and inference, as it helps avoid misleading conclusions that can arise from incomplete sampling.
congrats on reading the definition of Convergence diagnostics. now let's actually learn it.