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