Some classical inference procedures can be shown to be completely robust in theses classes of multivariate distributions. These findings are used in the practically relevant context of regression models. We present a robust bayesian analysis and indicate the links between classical and Bayesian results. In particular, for the regression model with i.i.d. errors up to a scale, a formal characterization is provided for both classical and Bayesian robustness results concerning inference on the regression parameters.
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Paper provided by Catholique de Louvain - Institut de statistique in its series Papers with number
9602.
Length: 18 pages Date of creation: 1996 Date of revision: Handle: RePEc:fth:louvis:9602
Contact details of provider: Postal: Universite Catholique de Louvain, Institut de Statistique, Voie du Roman Pays, 34 B-1348 Louvain- La-Neuve, Belgique.
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Find related papers by JEL classification: C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models
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