BIC Context Tree Estimation for Stationary Ergodic Processes
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Material Type |
Article
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Author(s) |
Talata, Z. (Author)
Duncan, T.E. (Author)
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Source Journal Info. |
Title:
IEEE Transactions on Information Theory
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Volume/ Issue No.: 2011/JUN V.57 N.6
Call No.:003.4505 ITI Location: Periodicals & References Hall - 2nd floor
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Physical Description |
p 3877 - 3886
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Subject Area/ Descriptors |
Computer
(12522)
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Abstract |
Context trees of arbitrary stationary ergodic processes with finite alphabets are considered. Such a process is not necessarily a Markov chain, so the context tree may be of infinite depth. Calculated from a sample of size n, the Bayesian information criterion (BIC) is shown to provide a strongly consistent estimator of the context tree of the process...
Full Abstract
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Journal:
IEEE Transactions on Information Theory
(1673)
Issu: 2011/JUN V.57 N.6
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