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We study the problem of two-sample comparisons with categorical data when the contingency table is sparsely populated. Classical methods, such as the Pearson's Chi-square test and the deviance test, ...
This paper deals with two-sample Kolmogorov-Smirnov test and its biasedness. This test is not unbiased in general in case of different sample sizes.
We introduce fully nonparametric two sample tests for testing the null hypothesis that the two samples come from the same distribution if the values are only indirectly given via current status censor...
We introduce fully nonparametric two sample tests for testing the null hypothesis that the two samples come from the same distribution if the values are only indirectly given via current status censor...
Testing and characterizing the difference between two data samples is of fundamen-tal interest in statistics. Existing methods such as Kolmogorov-Smirnov and Cramer-von-Mises tests do not scale well a...
We propose a two-sample test for the means of high-dimensional data when the data dimension is much larger than the sample size. Hotelling’s classical T 2 test does not work for this “large p, small...
We consider a sequential point estimation of the ratio of two exponential scale parameters. For a fully sequential sampling scheme, second order approximations are obtained to the expected sample size...
Asymptotic confidence intervals of location parameters are proposed in one- and two-sample models. These are robust procedures based on scale-invariant M-statistics. The one-sample procedures have the...
A convex combination of one-sample U-statistics was introduced by Toda and Yamato (2001) and its Edgeworth expansion was derived by Yamato et al. (2003). We introduce a convex combination of two-sampl...
Given two independent samples of non-negative random variables with unknown distribution functions F and G, respectively, we introduce and discuss two tests for the hypothesis that F is less than or ...

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