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Abstract Details
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Activity Number:
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301
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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| Abstract - #305898 |
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Title:
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Penalized Maximum Likelihood Methods in Process Estimation
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Author(s):
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Zsolt Talata*+
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Companies:
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University of Kansas
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Address:
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1460 Jayhawk Boulevard, Lawrence, KS, 66045-7523, United States
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Keywords:
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finite memory estimator ;
Markov approximation ;
infinite memory ;
rate of convergence ;
penalized maximum likelihood ;
stationary ergodic process
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Abstract:
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Stationary ergodic processes with finite alphabets are estimated by finite memory processes from a sample, an n-length realization of the process, where the memory depth of the estimator process is also estimated from the sample using penalized maximum likelihood (PML). Under some assumptions on the continuity rate and the assumption of non-nullness, a rate of convergence in d-bar distance is obtained, with explicit constants. The results show optimality of the PML Markov order estimator for not necessarily finite memory processes.
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Authors who are presenting talks have a * after their name.
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