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An adaptive, automatic multiple-case deletion technique for detecting influence in regression

Roberts, Steven; Zheng, Letian; Martin, Michael


Critical to any regression analysis is the identification of observations that exert a strong influence on the fitted regression model. Traditional regression influence statistics such as Cook's distance and DFFITS, each based on deleting single observations, can fail in the presence of multiple influential observations if these influential observations "mask" one another, or if other effects such as "swamping" occur. Masking refers to the situation where an observation reveals itself as...[Show more]

CollectionsANU Research Publications
Date published: 2014
Type: Journal article
Source: Technometrics
DOI: 10.1080/00401706.2014.946152


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