
SUMMARY Previous work on the use of gaps or spacings to test for uniformity of a sample has been in terms of distances between successive order statistics of the sample. This paper generalizes this notion of first-order gaps to mth-order gaps, and considers the sum of the logarithms of the mth-order gaps as a test statistic of uniformity. Asymptotic normality of this test statistic is shown under the null hypothesis of -uniformity, even when m grows at a moderate rate with the sample size. The test is compared with the most powerful test symmetric in the first-order gaps, and it is shown that the Pitman asymptotic relative efficiency increases for large m approximately linearly in m.
Asymptotic distribution theory in statistics, spacings, Asymptotic properties of nonparametric inference, Physical Sciences and Mathematics, logarithms, high, order, Nonparametric hypothesis testing
Asymptotic distribution theory in statistics, spacings, Asymptotic properties of nonparametric inference, Physical Sciences and Mathematics, logarithms, high, order, Nonparametric hypothesis testing
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