Convergence diagnostics refers to a set of techniques used to determine whether a statistical model has sufficiently converged to a stable solution after fitting, particularly in the context of Bayesian inference. These techniques help assess the reliability of the results produced by Markov Chain Monte Carlo (MCMC) methods, ensuring that the algorithm has explored the parameter space adequately and that the estimates are representative of the posterior distribution.
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