The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Stochastic Complexity
Abstract
SUMMARY: It is argued that all the useful information in observed data that can be extracted with a selected class of modeled distributions, will be obtained if we calculate the stochastic complexity, defined to be the shortest description length of the data. The same quantity also determines the greatest lower bound for prediction errors when the data are sequentially predicted. An abstract definition of stochastic complexity is given along with two fundamental theorems which justify the notion. Further, three explicit model selection criteria to approximate the stochastic complexity are described and the associated optimal models are interpreted to define asymptotically sufficient statistics for the data.
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Citations
Cites
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Schwarz, G. (1978) · The Annals of Statistics · doi:10.1214/aos/1176344136 · Cited by 47,033
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Cited by
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
Fisher information and stochastic complexity
Rissanen, J. J. (1996) · IEEE Transactions on Information Theory · doi:10.1109/18.481776 · Cited by 814
Self-citationModel Selection and the Principle of Minimum Description Length
Hansen, M. H., & Yu, B. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753168398 · Cited by 788
Akaike's Information Criterion and Recent Developments in Information Complexity
Bozdogan, H. (2000) · Journal of Mathematical Psychology · doi:10.1006/jmps.1999.1277 · Cited by 674
Why so many clustering algorithms: a position paper
Estivill-Castro, V. (2002) · ACM SIGKDD Explorations Newsletter · doi:10.1145/568574.568575 · Cited by 600
Metadata
- Authors
- Rissanen, J.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1987-07-01
- Volume
- 49
- Issue
- 3
- Pages
- 223-239
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W4240190281
- Cited by
- 339
- References
- 26
- FWCI
- 4.73
- Type
- journal article
- Language
- en
- Open access
- closed
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