ON APPROXIMATING THE DISTRIBUTIONS OF GOODNESS-OF-FIT TEST STATISTICS BASED ON THE EMPIRICAL DISTRIBUTION FUNCTION: THE CASE OF UNKNOWN PARAMETERS

DOI10.1142/S0219525909002131zbMath1170.62011arXiv0803.4322MaRDI QIDQ3636536

Lucia Alessi, Marco Capasso, Matteo Barigozzi, Giorgio Fagiolo

Publication date: 30 June 2009

Published in: Advances in Complex Systems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0803.4322

zbMATH Keywords

critical valuesempirical distribution functionCramér-von Mises statisticMonte-Carlo simulationsKolmogorov-Smirnov statisticAnderson-Darling statisticKuiper statistic

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Order statistics; empirical distribution functions (62G30) Monte Carlo methods (65C05) Approximations to statistical distributions (nonasymptotic) (62E17)

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Cites Work

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• THE PROBABILITY INTEGRAL TRANSFORMATION WHEN PARAMETERS ARE ESTIMATED FROM THE SAMPLE
• The Cramer-Smirnov Test in the Parametric Case

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