Hodges-Lehmann asymptotic efficiency of the Kolmogorov and Smirnov goodness-of-fit tests
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Abstract
One considers the Hodges-Lehmann asymptotic efficiency of the Kolmogorov and Smirnov goodness-of-fit tests, which measures the rate of the exponential decrease of the errors of the second kind, under a fixed significance level. It is shown that the Kolmogorov test is always asymptotically optimal in this sense, while the one-sided Smirnov test is asymptotically optimal under additional conditions imposed on the parametric family of distributions.
Keywords
Additional Condition Smirnov Test Parametric Family Fixed Significance Exponential Decrease
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© Plenum Publishing Corporation 1987