Robust estimation for ARMA models

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This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates based on a diagnostic procedure.
Published in at http://dx.doi.org/10.1214/07-AOS570 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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Statistics Theory, 62F35, 62M10 (Primary)

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http://salesiana.dossiersoluciones.com/handle/123456789/225443

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0904.0106
 http://arxiv.org/abs/0904.0106
 Annals of Statistics 2009, Vol. 37, No. 2, 816-840
 doi:10.1214/07-AOS570

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arXiv