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Activity Number: 83
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 4:00 PM to 5:50 PM
Sponsor: International Chinese Statistical Association
Abstract #320984 View Presentation
Title: A Class of Minimum Distance Estimators in AR(P) Models with Infinite Error Variance
Author(s): Xiaoyu Li* and Hira L. Koul
Companies: Auburn University and Michigan State University
Keywords: asymptotic normality ; Pareto-like tails distributions

In this note we establish asymptotic normality of a class of minimum distance estimators of autoregressive parameters when error variance is infinite, thereby extending the domain of their applications to a larger class of error distributions that includes a class of stable symmetric distributions having Pareto-like tails. These estimators are based on certain symmetrized randomly weighted residual empirical processes. In particular they include analogs of robustly weighted least absolute deviation and Hodges-Lehmann type estimators.

Authors who are presenting talks have a * after their name.

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