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Asymptotic Distribution Theory in Nonparametric Statistics
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The article was published on 1985-01-01 and is currently open access. It has received 54 citations till now. The article focuses on the topics: Asymptotic analysis & Asymptotic distribution.read more
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Empirical Process Techniques for Dependent Data
Herold Dehling,Walter Philipp +1 more
TL;DR: In this article, the authors provide a survey of classical and modern techniques in the study of empirical processes of dependent data, and provide necessary technical tools like correlation and moment inequalities, and prove central limit theorems for partial sums.
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A universal result in almost sure central limit theory
István Berkes,Endre Csáki +1 more
TL;DR: In this article, it was shown that every weak limit theorem for independent random variables, subject to minor technical conditions, has an analogous almost sure version of a.s. limit.
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Nonparametric validation of similar distributions and assessment of goodness of fit
Axel Munk,Claudia Czado +1 more
TL;DR: In this paper, an asymptotic test based on an (x-trimmed version of Mallows distance r,(F, G) between F and G is suggested, thus demonstrating the similarity of F and g within a pre-assigned r, (F,G) neighbourhood at a controlled type I error rate.
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Qualitative and infinitesimal robustness of tail-dependent statistical functionals
TL;DR: A new notion of qualitative robustness is introduced that applies also to tail-dependent statistical functionals and that allows us to compare statistical functional in regards to their degree of robustness by means of new versions of the Hampel theorem.
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Rank statistics under dependent observations and applications to factorial designs
Edgar Brunner,Manfred Denker +1 more
TL;DR: For multivariate designs of independent random vectors of varying dimensions, the asymptotic variance of rank statistics has been shown to be normal even in case the dimensions tend to infinity as discussed by the authors.