Rates of convergence in the central limit theorem for linear statistics of martingale differences

Abstract : In this paper, we give rates of convergence for minimal distances between linear statistics of martingale differences and the limiting Gaussian distribution. In particular the results apply to the partial sums of (possibly long range dependent) linear processes, and to the least squares estimator in some parametric regression models.
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Article dans une revue
Stochastic Processes and their Applications, Elsevier, 2011, 121, pp.1013-1043
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https://hal.archives-ouvertes.fr/hal-00685923
Contributeur : Jérôme Dedecker <>
Soumis le : vendredi 6 avril 2012 - 13:09:49
Dernière modification le : mardi 11 octobre 2016 - 12:02:49

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  • HAL Id : hal-00685923, version 1

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Jérôme Dedecker, Florence Merlevède. Rates of convergence in the central limit theorem for linear statistics of martingale differences. Stochastic Processes and their Applications, Elsevier, 2011, 121, pp.1013-1043. <hal-00685923>

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