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Fisher information and stochastic complexity

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1 Author(s)
Rissanen, J. ; IBM Almaden Res. Center, San Jose, CA, USA

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

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Information Theory, IEEE Transactions on  (Volume:42 ,  Issue: 1 )