Abstract Details
Activity Number:
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691
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Type:
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Contributed
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Date/Time:
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Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract - #310001 |
Title:
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Memory Depth Identification for Real-Valued Processes
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Author(s):
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Zsolt Talata*+ and Roberto Oliveira
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Companies:
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University of Kansas and IMPA
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Keywords:
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ergodic processes ;
Markov chains ;
Markov order ;
order estimation ;
strong consistency ;
computational complexity
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Abstract:
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Stationary ergodic processes with values from a finite interval are considered. A certain mixing condition is assumed, which is satisfied by, for example, the autoregressive processes. The memory depth of the process is estimated from a sample, an n-length realization of the process. An estimator of the memory depth is presented; its strong consistency is proved and the computational complexity of an algorithm to compute the estimator is determined.
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Authors who are presenting talks have a * after their name.
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