On Approximating the Distributions of goodness-of-Fit Test Statistics Based on the Empirical Distribution Function: the Case of Unknown Parameters

@article{Capasso2009OnAT,
  title={On Approximating the Distributions of goodness-of-Fit Test Statistics Based on the Empirical Distribution Function: the Case of Unknown Parameters},
  author={Marco Capasso and Lucia Alessi and Matteo Barigozzi and Giorgio Fagiolo},
  journal={Adv. Complex Syst.},
  year={2009},
  volume={12},
  pages={157-167}
}
This paper discusses some problems possibly arising when approximating via Monte-Carlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to re-estimate unknown parameters on each simulated Monte-Carlo sample — and thus avoiding to employ this information to build the test statistic — may lead to wrong, overly-conservative. Furthermore, we present some simple examples suggesting that the impact of this possible… Expand
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