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Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions |
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| Authors: | Shuangzhe Liu Víctor Leiva Tiefeng Ma Alan Welsh |
| Institution: | 1.Faculty of Education, Science, Technology and Mathematics,University of Canberra,Canberra,Australia;2.Faculty of Engineering and Sciences,Adolfo Ibá?ez University,Vi?a del Mar,Chile;3.Institute of Statistics,University of Valparaíso,Valparaíso,Chile;4.School of Statistics,Southwestern University of Finance and Economics,Chengdu,China;5.Mathematical Sciences Institute,Australian National University,Canberra,Australia |
| Abstract: | 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. |
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