Recursive estimation of possibly misspecified MA(1) models: Convergence of a general algorithm

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dc.creatorCantor, James L.
dc.creatorFindley, David F.
dc.date2007-02-26
dc.date.accessioned2026-07-07T08:08:46Z
dc.date.available2026-07-07T08:08:46Z
dc.descriptionWe introduce a recursive algorithm of conveniently general form for estimating the coefficient of a moving average model of order one and obtain convergence results for both correct and misspecified MA(1) models. The algorithm encompasses Pseudolinear Regression (PLR--also referred to as AML and $RML_1$) and Recursive Maximum Likelihood ($RML_2$) without monitoring. Stimulated by the approach of Hannan (1980), our convergence results are obtained indirectly by showing that the recursive sequence can be approximated by a sequence satisfying a recursion of simpler (Robbins-Monro) form for which convergence results applicable to our situation have recently been obtained.
dc.descriptionPublished at http://dx.doi.org/10.1214/074921706000000932 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0702764
dc.identifierhttp://arxiv.org/abs/math/0702764
dc.identifierIMS Lecture Notes Monograph Series 2006, Vol. 52, 20-47
dc.identifierdoi:10.1214/074921706000000932
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/131377
dc.subjectStatistics Theory
dc.subject62M10 (Primary) 62L20 (Secondary)
dc.titleRecursive estimation of possibly misspecified MA(1) models: Convergence of a general algorithm
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