Fisher information and stochastic complexity

By taking into account the Fisher information and removing an inherent redundancy in earlier two-part codes, a sharper code length as the stochastic complexity and the associated universal process are derived for a class of parametric processes. The main condition required is that the maximum-likeli...

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Bibliographic Details
Published in:IEEE transactions on information theory 1996-01, Vol.42 (1), p.40-47
Main Author: Rissanen, J.J.
Format: Article
Language:English
Subjects:
Bayesian methods
Channel capacity
Cryptography
Entropy
Information theory
Markov processes
Mutual information
Senior members
Statistics
Stochastic models
Stochastic processes
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Summary:By taking into account the Fisher information and removing an inherent redundancy in earlier two-part codes, a sharper code length as the stochastic complexity and the associated universal process are derived for a class of parametric processes. The main condition required is that the maximum-likelihood estimates satisfy the central limit theorem. The same code length is also obtained from the so-called maximum-likelihood code.
ISSN:0018-9448
1557-9654
DOI:10.1109/18.481776