dc.contributor.author
Bagheri, Arezoo
dc.contributor.author
Midi, Habshah
dc.identifier
https://ddd.uab.cat/record/132927
dc.identifier
urn:oai:ddd.uab.cat:132927
dc.identifier
urn:oai:raco.cat:article/294377
dc.identifier
urn:articleid:20138830v39n1p51
dc.description.abstract
High leverage collinearity influential observations are those high leverage points that change the multicollinearity pattern of a data. It is imperative to identify these points as they are responsible for misleading inferences on the fitting of a regression model. Moreover, identifying these observations may help statistics practitioners to solve the problem of multicollinearity, which is caused by high leverage points. A diagnostic plot is very useful for practitioners to quickly capture abnormalities in a data. In this paper, we propose new diagnostic plots to identify high leverage collinearity influential observations. The merit of our proposed diagnostic plots is confirmed by some well-known examples and Monte Carlo simulations.
dc.format
application/pdf
dc.relation
SORT : statistics and operations research transactions ; Vol. 39 Núm. 1 (January-June 2015), p. 51-70
dc.rights
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
dc.rights
https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject
Collinearity influential observation
dc.subject
High lever-age points
dc.subject
Multicollinearity
dc.subject
Diagnostic robust generalized potential
dc.title
Diagnostic plot for the identification of high leverage collinearity-influential observations
