The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Mixtures of g Priors for Bayesian Variable Selection
Abstract
Zellner's g prior remains a popular conventional prior for use in Bayesian variable selection, despite several undesirable consistency issues. In this article we study mixtures of g priors as an alternative to default g priors that resolve many of the problems with the original formulation while maintaining the computational tractability that has made the g prior so popular. We present theoretical properties of the mixture g priors and provide real and simulated examples to compare the mixture formulation with fixed g priors, empirical Bayes approaches, and other default procedures. Please see Arnold Zellner's letter and the author's response.
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Cites
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McQuarrie, D. A. (1966) · American Journal of Physics · doi:10.1119/1.1972842 · Cited by 40,433
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Variable Selection via Gibbs Sampling
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Calibration and empirical Bayes variable selection
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Cited by
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Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009) · Psychonomic Bulletin & Review · doi:10.3758/pbr.16.2.225 · Cited by 3,688
Sure Independence Screening for Ultrahigh Dimensional Feature Space
Fan, J., & Lv, J. (2008) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2008.00674.x · Cited by 2,711
Using Bayes to get the most out of non-significant results
Dienes, Z. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00781 · Cited by 1,998
Default Bayes factors for ANOVA designs
Rouder, J. N., Morey, R. D., Speckman, P. L., & Province, J. M. (2012) · Journal of Mathematical Psychology · doi:10.1016/j.jmp.2012.08.001 · Cited by 1,800
Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications
Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., et al. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-017-1343-3 · Cited by 1,627
Metadata
- Authors
- Liang, F., Paulo, R., Molina, G., Clyde, M. A., & Berger, J. O.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 2008-03-01
- Volume
- 103
- Issue
- 481
- Pages
- 410-423
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2020389170
- Cited by
- 1,089
- References
- 4
- FWCI
- 39.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liang, F., Paulo, R., Molina, G., Clyde, M. A., & Berger, J. O. (2008). Mixtures of g Priors for Bayesian Variable Selection. Journal of the American Statistical Association. https://doi.org/10.1198/016214507000001337
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