A Bayesian mixture of lasso regressions with t-errors
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DOI: 10.1016/j.csda.2014.03.018
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- Pierre Del Moral & Arnaud Doucet & Ajay Jasra, 2006. "Sequential Monte Carlo samplers," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(3), pages 411-436, June.
- Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
- Park, Trevor & Casella, George, 2008. "The Bayesian Lasso," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 681-686, June.
- Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2009. "Regression density estimation using smooth adaptive Gaussian mixtures," Journal of Econometrics, Elsevier, vol. 153(2), pages 155-173, December.
- Chung, Yeonseung & Dunson, David B., 2009. "Nonparametric Bayes Conditional Distribution Modeling With Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1646-1660.
- Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
- Sinae Kim & Mahlet G. Tadesse & Marina Vannucci, 2006. "Variable selection in clustering via Dirichlet process mixture models," Biometrika, Biometrika Trust, vol. 93(4), pages 877-893, December.
- Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342, June.
- Raftery, Adrian E. & Dean, Nema, 2006. "Variable Selection for Model-Based Clustering," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 168-178, March.
- Khalili, Abbas & Chen, Jiahua, 2007. "Variable Selection in Finite Mixture of Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1025-1038, September.
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Cited by:
- Lee, Kuo-Jung & Feldkircher, Martin & Chen, Yi-Chi, 2021. "Variable selection in finite mixture of regression models with an unknown number of components," Computational Statistics & Data Analysis, Elsevier, vol. 158(C).
- Zhang, Yifan & Fong, Duncan K.H. & DeSarbo, Wayne S., 2021. "A generalized ordinal finite mixture regression model for market segmentation," International Journal of Research in Marketing, Elsevier, vol. 38(4), pages 1055-1072.
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Keywords
Mixture of regressions; Variable selection; Particle Markov chain Monte Carlo;All these keywords.
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