Simulations and modes of convergence
Read OriginalThe article critiques the common practice of reporting empirical means and standard deviations in simulations verifying asymptotic theory. It argues that convergence in distribution does not guarantee convergence of moments, and that quantile-based statistics (like medians and MAD) are more appropriate and robust summaries for assessing the practical utility of approximations like the Central Limit Theorem.
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