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Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics

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We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.
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Keywords: computational statistics; elliptically contoured distributions; generalized least squares; local influence method; maximum-likelihood method; mixed estimation

Document Type: Research Article

Affiliations: 1: Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Viña del Mar, Chile 2: Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia 3: Statistics and Mathematics College, Yunnan University of Finance and Economics, Kunming, People's Republic of China 4: Department of Statistics, Universidade Federal de Pernambuco, Recife, Brazil

Publication date: March 11, 2016

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