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A note on the generalized information criterion for choice of a model
Abstract
One way of selecting models is to choose that model for which the maximized log likelihood minus a multiple of the number of parameters estimated is a maximum. This note explores the choice of values for the multiplier, with the value one corresponding to Akaike's information criterion. The relationship with Bayesian procedures is mentioned.
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Cited by
Bayesian Measures of Model Complexity and Fit
Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van Der Linde, A. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00353 · Cited by 151
Bozdogan, H. (1987) · Psychometrika · doi:10.1007/bf02294361 · Cited by 4,468
Vrieze, S. I. (2012) · Psychological Methods · doi:10.1037/a0027127 · Cited by 1,948
Sensitivity and specificity of information criteria
(2019) · doi:10.1093/bib/bbz016 · Cited by 718
Predictive value of statistical models.
Van Houwelingen, J. C., & Le Cessie, S. (1990) · Statistics in Medicine · doi:10.1002/sim.4780091109 · Cited by 621
Metadata
- Authors
- ATKINSON, A. C.
- Venue
- Biometrika
- Publisher
- Oxford University Press (OUP)
- Published
- 1980
- Volume
- 67
- Issue
- 2
- Pages
- 413-418
- ISSN
- 0006-3444 (ISSN-L)
- 1464-3510
- OpenAlex
- W1973464501
- Cited by
- 262
- References
- 0
- FWCI
- 4.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- ATKINSON, A. C. (1980). A note on the generalized information criterion for choice of a model. Biometrika. https://doi.org/10.1093/biomet/67.2.413
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