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Asymptotic Properties of Criteria for Selection of Variables in Multiple Regression
Open accessAbstract
In normal linear regression analysis, many model selection rules proposed from various viewpoints are available. For the information criteria AIC, FPE, $C_p$, PSS and BIC, the asymptotic distribution of the selected model and the asymptotic quadratic risk based on each criterion are explicitly obtained.
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Cited by
Posada, D., & Buckley, T. R. (2004) · Systematic Biology · doi:10.1080/10635150490522304 · Cited by 3,927
A survey of cross-validation procedures for model selection
Arlot, S., & Celisse, A. (2010) · Statistics Surveys · doi:10.1214/09-ss054 · Cited by 3,522
Vrieze, S. I. (2012) · Psychological Methods · doi:10.1037/a0027127 · Cited by 1,948
(2004) · doi:10.1177/0049124103262065 · Cited by 906
Yadav, S., & Shukla, S. (2016) · 2016 IEEE 6th International Conference on Advanced Computing (IACC) · doi:10.1109/iacc.2016.25 · Cited by 773
Metadata
- Authors
- Nishii, R.
- Venue
- The Annals of Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1984-06-01
- Volume
- 12
- Issue
- 2
- ISSN
- 0090-5364 (ISSN-L)
- OpenAlex
- W1983351268
- Cited by
- 335
- References
- 0
- FWCI
- 1.75
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Nishii, R. (1984). Asymptotic Properties of Criteria for Selection of Variables in Multiple Regression. The Annals of Statistics. https://doi.org/10.1214/aos/1176346522
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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