Influence Assessment in an Heteroscedastic Errors-in-Variables Model

dc.creatorGalea, Manuel
dc.creatorCastro, Mário de
dc.date.accessioned2013-10-29T14:21:05Z
dc.date.accessioned2018-07-04T16:02:56Z
dc.date.available2013-10-29T14:21:05Z
dc.date.available2018-07-04T16:02:56Z
dc.date.created2013-10-29T14:21:05Z
dc.date.issued2012
dc.identifierCommunications in Statistics - Theory and Methods, Philadelphia, v. 41, n. 8, supl. 1, Part 3, p. 1350-1363, may, 2012
dc.identifier0361-0926
dc.identifierhttp://www.producao.usp.br/handle/BDPI/36374
dc.identifier10.1080/03610926.2010.543301
dc.identifierhttp://dx.doi.org/10.1080/03610926.2010.543301
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1630922
dc.description.abstractThe main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.
dc.languageeng
dc.publisherTaylor and Francis Group, LLC
dc.publisherPhiladelphia
dc.relationCommunications in Statistics - Theory and Methods
dc.rightsCopyright Taylor and Francis Group, LLC
dc.rightsrestrictedAccess
dc.subjectCASE DELETION
dc.subjectEM ALGORITHM
dc.subjectEQUATION-ERROR MODELS
dc.subjectERRORS-IN-VARIABLES MODELS
dc.subjectLOCAL INFLUENCE
dc.titleInfluence Assessment in an Heteroscedastic Errors-in-Variables Model
dc.typeArtículos de revistas


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