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In this paper, we consider moderate deviations for Good's coverage estimator. The moderate deviation principle and the self-normalized moderate deviation principle for Good's coverage estimator are es...
The delta method is a popular and elementary tool for deriving limiting distributions of transformed statistics, while applications of asymptotic distributions do not allow one to obtain desirable a...
We obtain uniform (in time) moderate deviations for the functional empirical process ofa general state space Markov chain under the geometric ergodicity assumption, and a regularity condition for t...
Motivated by the study of dependent random variables by coupling with independent blocks of variables,we obtain first sufficient conditions for the moderate deviation principle in its functional form ...
We prove that the Moderate Deviation Principle (MDP) holds for the trajectory of a locally square integrable martingale with bounded jumps as soon as its quadratic covariation, properly scaled, conver...
Let X , X1, X 2 , ... be i.i.d. R d-valued random variables. We prove large and moderate deviations for Hotelling's T2-statistic when X is in the generalized domain of attraction of the normal law.
Let X , X1, X 2 , ... be i.i.d. R d-valued random variables. We prove large and moderate deviations for Hotelling's T2-statistic when X is in the generalized domain of attraction of the normal law.
In this paper, we prove large deviations principle for the Nadaraya-Watson estimator and for the semi-recursive kernel estimator of the regression in the multidimensional case. Under suitable condi...

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