文章基本信息

标题：Influence diagnostics in exponentiated-Weibull regression models with censored data
本地全文：下载
作者：Edwin M. M. Ortega ; Vicente G. Cancho ; Heleno Bolfarine 等
期刊名称：SORT-Statistics and Operations Research Transactions
印刷版ISSN：2013-8830
出版年度：2006
卷号：30
期号：2
页码：171-192
语种：English
出版社：SORT- Statistics and Operations Research Transactions
摘要：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.