HAL : hal-00627557, version 1

arXiv : 1109.6493

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Improved estimation in a non-Gaussian parametric regression

Evgeny Pchelintsev 1

(29/09/2011)

The paper considers the problem of estimating the parameters in a continuous time regression model with a non-Gaussian noise of pulse type. The noise is specified by the Ornstein-Uhlenbeck process driven by the mixture of a Brownian motion and a compound Poisson process. Improved estimates for the unknown regression parameters, based on a special modification of the James-Stein procedure with smaller quadratic risk than the usual least squares estimates, are proposed. The developed estimation scheme is applied for the improved parameter estimation in the discrete time regression with the autoregressive noise depending on unknown nuisance parameters.

1 :	Laboratoire de Mathématiques Raphaël Salem (LMRS)
	CNRS : UMR6085 – Université de Rouen

Domaine

:

Mathématiques/Statistiques Statistiques/Théorie

Mots Clés : Non-Gaussian parametric regression – Improved estimates – Pulse noise – Ornstein-Uhlenbeck process – Quadratic risk – Autoregressive noise

hal-00627557, version 1

http://hal.archives-ouvertes.fr/hal-00627557

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Contributeur : Evgeny Pchelintsev <>

Soumis le : Jeudi 29 Septembre 2011, 08:54:08

Dernière modification le : Jeudi 29 Septembre 2011, 13:48:05