The empirical distribution function for dependent variables : asymptotic and nonasymptotic results in 𝕃 p
ESAIM: Probability and Statistics, Tome 11 (2007), pp. 102-114.

Considering the centered empirical distribution function F n -F as a variable in 𝕃 p (μ), we derive non asymptotic upper bounds for the deviation of the 𝕃 p (μ)-norms of F n -F as well as central limit theorems for the empirical process indexed by the elements of generalized Sobolev balls. These results are valid for a large class of dependent sequences, including non-mixing processes and some dynamical systems.

DOI : 10.1051/ps:2007009
Classification : 60F10, 62G30
Mots-clés : deviation inequalities, weak dependence, Cramér-von Mises statistics, empirical process, expanding maps
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     title = {The empirical distribution function for dependent variables : asymptotic and nonasymptotic results in ${\mathbb {L}}^p$},
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Dedecker, Jérôme; Merlevède, Florence. The empirical distribution function for dependent variables : asymptotic and nonasymptotic results in ${\mathbb {L}}^p$. ESAIM: Probability and Statistics, Tome 11 (2007), pp. 102-114. doi : 10.1051/ps:2007009. http://archive.numdam.org/articles/10.1051/ps:2007009/

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