Regularization in Regression : Comparing Bayesian and Frequentist Methods in a Poorly Informative Situation
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- Zou, Hui, 2006. "The Adaptive Lasso and Its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1418-1429, December.
- Philips, R. & Guttman, I., 1998. "A new criterion for variable selection," Statistics & Probability Letters, Elsevier, vol. 38(1), pages 11-19, May.
- P. J. Brown & M. Vannucci & T. Fearn, 1998. "Multivariate Bayesian variable selection and prediction," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(3), pages 627-641.
- Fernandez, Carmen & Ley, Eduardo & Steel, Mark F. J., 2001.
"Benchmark priors for Bayesian model averaging,"
Journal of Econometrics, Elsevier, vol. 100(2), pages 381-427, February.
- Carmen Fernández & Eduardo Ley & Mark F. J. Steel, "undated". "Benchmark priors for Bayesian Model averaging," Working Papers 98-06, FEDEA.
- Carmen Fernandez & Eduardo Ley & Mark F.J. Steel, 1998. "Benchmark Priors for Bayesian Model Averaging," Econometrics 9804001, University Library of Munich, Germany, revised 08 Oct 2001.
- Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998. "Benchmark priors for Bayesian model averaging," Edinburgh School of Economics Discussion Paper Series 26, Edinburgh School of Economics, University of Edinburgh.
- Carmen Fernandez & Eduardo Ley & Mark F J Steel, 1998. "Benchmark priors for Bayesian model averaging," Edinburgh School of Economics Discussion Paper Series 66, Edinburgh School of Economics, University of Edinburgh.
- Smith, Michael & Kohn, Robert, 1996.
"Nonparametric regression using Bayesian variable selection,"
Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
- Smith, M. & Kohn, R., "undated". "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
- Casella, George & Moreno, Elias, 2006. "Objective Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 157-167, March.
- repec:dau:papers:123456789/1906 is not listed on IDEAS
- Park, Trevor & Casella, George, 2008. "The Bayesian Lasso," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 681-686, June.
- repec:dau:papers:123456789/857 is not listed on IDEAS
- Liang, Feng & Paulo, Rui & Molina, German & Clyde, Merlise A. & Berger, Jim O., 2008. "Mixtures of g Priors for Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 410-423, March.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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