The M-estimator in a multi-phase random nonlinear model

dc.creatorCiuperca, Gabriela
dc.date2007-06-01
dc.date2008-09-22
dc.date.accessioned2026-07-07T10:03:53Z
dc.date.available2026-07-07T10:03:53Z
dc.descriptionThis paper considers M-estimation of a nonlinear regression model with multiple change-points occuring at unknown times. The multi-phase random design regression model, discontinuous in each change-point, have an arbitrary error $ε$. In the case when the number of jumps is known, the M-estimator of locations of breaks and of regression parameters are studied. These estimators are consistent and the distribution of the regression parameter estimators is Gaussian. The estimator of each change-point converges, with the rate $n^{-1}$, to the smallest minimizer of the independent compound Poisson processes. The results are valid for a large class of error distributions.
dc.description19 pages
dc.identifierhttps://arxiv.org/abs/0706.0153
dc.identifierhttp://arxiv.org/abs/0706.0153
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/169460
dc.subjectStatistics Theory
dc.subjectProbability
dc.subjectMethodology
dc.titleThe M-estimator in a multi-phase random nonlinear model
dc.typetext

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