Influence Assessment in an Heteroscedastic Errors-in-Variables Model

dc.creatorGalea Rojas, Manuel Jesús
dc.creatorCastro, Mario de
dc.date.accessioned2024-04-18T21:11:40Z
dc.date.accessioned2024-05-02T19:41:01Z
dc.date.available2024-04-18T21:11:40Z
dc.date.available2024-05-02T19:41:01Z
dc.date.created2024-04-18T21:11:40Z
dc.date.issued2012
dc.identifier10.1080/03610926.2010.543301
dc.identifier0361-0926
dc.identifierhttps://doi.org/10.1080/03610926.2010.543301
dc.identifierhttps://repositorio.uc.cl/handle/11534/85244
dc.identifierWOS:000304525700003
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9272845
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.languageen
dc.publisherTAYLOR & FRANCIS INC
dc.rightsacceso restringido
dc.subjectCase deletion
dc.subjectEM algorithm
dc.subjectEquation-error models
dc.subjectErrors-in-variables models
dc.subjectLinear mixed models
dc.subjectLocal influence
dc.subjectIncomplete-Data
dc.subjectRegression
dc.titleInfluence Assessment in an Heteroscedastic Errors-in-Variables Model
dc.typeartículo


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