Robust estimation for ARMA models

dc.creatorMuler, Nora
dc.creatorPeña, Daniel
dc.creatorYohai, Víctor J.
dc.date2009-04-01
dc.date.accessioned2026-07-07T12:59:01Z
dc.date.available2026-07-07T12:59:01Z
dc.descriptionThis 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.
dc.descriptionPublished 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)
dc.identifierhttps://arxiv.org/abs/0904.0106
dc.identifierhttp://arxiv.org/abs/0904.0106
dc.identifierAnnals of Statistics 2009, Vol. 37, No. 2, 816-840
dc.identifierdoi:10.1214/07-AOS570
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/225443
dc.subjectStatistics Theory
dc.subject62F35, 62M10 (Primary)
dc.titleRobust estimation for ARMA models
dc.typetext

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