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Article Dans Une Revue Stochastic Processes and their Applications Année : 2011

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

Résumé

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.

Dates et versions

hal-00685923 , version 1 (06-04-2012)

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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, 2011, 121 (5), pp.1013-1043. ⟨10.1016/j.spa.2011.01.005⟩. ⟨hal-00685923⟩
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