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Abstract Details

Activity Number: 349
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #308466
Title: Alternative Bayesian Formulation for Robustness to Outliers
Author(s): Martin Heller*+
Companies: Unemployed
Address: 4621 Lemongrass Lane, Durham, NC, 27713,
Keywords: Robust Bayesian Analysis ; outliers ; epsilon contamination ; Robust Regression ; minimum distance estimators
Abstract:

We present a class of alternative posterior distributions which greatly increase robustness to outliers. The formulation of this method along with reasoning and establishment of several desired results including consistency will be presented. The advantage of this method is the ability to adapt to outliers without modifying the prior of the distribution space or data model. There is also no need to perform a sensitivity analysis followed by the removal of data. We give evidence of the efficacy through simulations with conjugate gradient classes and linear regression models. Although applied for increased robustness to outliers the alternative formulation is general and can be used for most Bayesian analysis.


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