Fisher information and stochastic complexity

Author

Rissanen, Jorma J.

Author_Institution

IBM Almaden Res. Center, San Jose, CA, USA

Volume

Issue

fYear

1996

fDate

1/1/1996 12:00:00 AM

Firstpage

Lastpage

Abstract

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

Keywords

codes; computational complexity; information theory; maximum likelihood estimation; stochastic processes; Fisher information; central limit theorem; code length; maximum-likelihood code; maximum-likelihood estimate; parametric processes; redundancy; stochastic complexity; two-part codes; universal process; Bayesian methods; Channel capacity; Entropy; Helium; Information theory; Markov processes; Mutual information; Senior members; Statistics; Stochastic processes;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.481776

Filename

481776

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1245240