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
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elliptically contoured distributions;
generalized least squares;
local influence method;
Document Type: Research Article
Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Viña del Mar, Chile
Faculty of Education, Science, Technology and Mathematics, University of Canberra, Canberra, Australia
Statistics and Mathematics College, Yunnan University of Finance and Economics, Kunming, People's Republic of China
Department of Statistics, Universidade Federal de Pernambuco, Recife, Brazil
March 11, 2016