The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Methods and Criteria for Model Selection
Open accessAbstract
Model selection is an important part of any statistical analysis and, indeed, is central to the pursuit of science in general. Many authors have examined the question of model selection from both frequentist and Bayesian perspectives, and many tools for selecting the “best model” have been suggested in the literature. This paper considers the various proposals from a Bayesian decision–theoretic perspective.
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Citations
Cites
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
The Jackknife, the Bootstrap and Other Resampling Plans
Efron, B. (1982) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611970319 · Cited by 8,120
Variable Selection via Gibbs Sampling
George, E. I., & McCulloch, R. E. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10476353 · Cited by 2,828
The Relationship Between Variable Selection and Data Agumentation and a Method for Prediction
Allen, D. M. (1974) · Technometrics · doi:10.1080/00401706.1974.10489157 · Cited by 1,469 · cited 1×
“The sum of the squared deleted residuals is the predicted residual sum of squares (Allen 1974).”
BackgroundModel Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window
Madigan, D., & Raftery, A. E. (1994) · Journal of the American Statistical Association · doi:10.1080/01621459.1994.10476894 · Cited by 1,205
Calibration and empirical Bayes variable selection
George, E. (2000) · Biometrika · doi:10.1093/biomet/87.4.731 · Cited by 520
Cited by
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
Woolcott, O. O., & Bergman, R. N. (2018) · Scientific Reports · doi:10.1038/s41598-018-29362-1 · Cited by 399
A review of automatic selection methods for machine learning algorithms and hyper-parameter values
Luo, G. (2016) · Network Modeling Analysis in Health Informatics and Bioinformatics · doi:10.1007/s13721-016-0125-6 · Cited by 357
Elk calf survival and mortality following wolf restoration to Yellowstone National Park
Barber-Meyer, S. M., Mech, L. D., & White, P. J. (2008) · Wildlife Monographs · doi:10.2193/2008-004 · Cited by 208
Metadata
- Authors
- Kadane, J. B., & Lazar, N. A.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 2004-03
- Volume
- 99
- Issue
- 465
- Pages
- 279-290
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2085890860
- Cited by
- 429
- References
- 6
- FWCI
- 13.12
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
