The extended two-sample problem: nonparametric case
TLDR
In this paper, the classical two-sample problem is extended to the case where the distribution functions of the observable random variables are specified functions of unknown distribution functions and the null hypotheses to be tested or the parameters to be estimated relate to these unknown distributions.About:
This article is published in Journal of Statistical Planning and Inference.The article was published on 1979-01-01 and is currently open access. It has received 4 citations till now. The article focuses on the topics: Asymptotic distribution & Random variable.read more
Citations
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Estimating with partial statistics the parameters of ergodic finite Markov sources
Neri Merhav,Jacob Ziv +1 more
TL;DR: Parameter estimation based on data emitted from a finite ergodic Markov source is discussed and an asymptotically optimal estimator is suggested for the case where the parametric model is completely known.
Estimation of general parameters using progressively truncated u-statistics
TL;DR: DelDelong as mentioned in this paper developed a method for truncating generalized twosample u-statistics progressively in time, and the asymptotic distributional properties of these estimators and processes are studied and conditions are imposed which guarantee large-sample weak convergence to Gaussian I pJ::'ocesses.
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A formula for P(bi≤Ri≤ai, 1≤i≤m) under a general class of alternatives
B. R. Handa,Sri Gopal Mohanty +1 more
TL;DR: In this article, an alternative expression for the same probability is obtained which is computationally a substantial improvement on Steck's result, where Ri denotes the rank of Xi in the combined order sample.
References
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Estimates of Location Based on Rank Tests
J. L. Hodges,Erich L. Lehmann +1 more
TL;DR: Rank tests such as the two Wilcoxon tests or the Kruskal-Wallis H-test have been shown to be more robust against gross errors than that of the t-and F-tests, even in the rare case in which the suspicion of the possibility of gross errors is unfounded.
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The Power of Rank Tests
E. L. Lehmann,E. L. Lehmann +1 more
TL;DR: In this article, simple nonparametric classes of alternatives are defined for various non-parametric hypotheses and the power of a number of such tests against these alternatives is obtained and illustrated with some numerical results.
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Asymptotic normality and efficiency of certain nonparametric test statistics
TL;DR: In this paper, it was shown for all alternative hypotheses that the FisherYates-Terry-Hoeffding cl-statistic is asymptotically normal and the test for translation based on it is at least as efficient as the t-test.
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Asymptotic Normality of Simple Linear Rank Statistics Under Alternatives II
Václav Dupač,Jaroslav Hájek +1 more
TL;DR: In this paper, the requirements concerning the scores-generating function are relaxed to a minimum: they assume that this function is a difference of two non-decreasing and square integrable functions.