A unified error statistic E-hat measures information lost to Monte Carlo noise in hierarchical Bayesian inference, with a recommended cutoff of 0.2 bits.
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When (not) to trust Monte Carlo approximations for hierarchical Bayesian inference
A unified error statistic E-hat measures information lost to Monte Carlo noise in hierarchical Bayesian inference, with a recommended cutoff of 0.2 bits.