Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions

Shuangzhe Liu, Víctor Leiva, Tiefeng Ma, Alan Welsh

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

11 Citas (Scopus)

Resumen

The local influence method has proven to be a useful and powerful tool for detecting influential observations on the estimation of model parameters. This method has been widely applied in different studies related to econometric and statistical modelling. We propose a methodology based on the Lagrange multiplier method with a linear penalty function to assess local influence in the possibly heteroskedastic linear regression model with exact restrictions. The restricted maximum likelihood estimators and information matrices are presented for the postulated model. Several perturbation schemes for the local influence method are investigated to identify potentially influential observations. Three real-world examples are included to illustrate and validate our methodology.

Idioma originalInglés
Páginas (desde-hasta)227-249
Número de páginas23
PublicaciónStatistical Methods and Applications
Volumen25
N.º2
DOI
EstadoPublicada - 1 jun 2016
Publicado de forma externa

Huella

Profundice en los temas de investigación de 'Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions'. En conjunto forman una huella única.

Citar esto