This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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31
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #308073 |
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Title:
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Asymptotics of Self-Normalized Linear Processes with Long Memory
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Author(s):
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Hailin Sang*+ and Magda Peligrad
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Companies:
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National Institute of Statistical Sciences and University of Cincinnati
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Address:
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19 T.W. Alexander Drive, Research Triangle Park, NC, 27709-4006, U.S.A
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Keywords:
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linear processes ;
long memory ;
invariance principle ;
fractional Brownian motion ;
domain of normal attraction ;
integrated processes
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Abstract:
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In this paper we study the central limit theorem in its functional form for time series with long memory having independent innovations with infinite second moment. For the sake of applications we derive the self-normalized version of this theorem. The study is motivated by models arising in economical applications where often the linear processes have long memory, the innovations have long tails and coefficients are not summable.
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