Influence diagnostics in exponentiated-Weibull regression models with censored data.
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Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2099/3793
Tipus de documentArticle
Data publicació2006
EditorInstitut d'Estadística de Catalunya
Condicions d'accésAccés obert
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continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement-NoComercial-SenseObraDerivada 2.5 Espanya
Abstract
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting
influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better.
CitacióOrtega, Edwin M. M.; Cancho, Vicente G.; Bolfarine, Heleno. "Influence diagnostics in exponentiated-Weibull regression models with censored data". SORT, 2006, Vol. 30, núm. 2
ISSN1696-2281
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