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Debashis Chatterjee, Trisha Maitra & Sourabh Bhattacharya. (2020) A Short Note on Almost Sure Convergence of Bayes Factors in the General Set-Up. The American Statistician 74:1, pages 17-20.
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David Rossell & Francisco J. Rubio. (2018) Tractable Bayesian Variable Selection: Beyond Normality. Journal of the American Statistical Association 113:524, pages 1742-1758.
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Vu Dinh, Ann E. Rundell & Gregery T. Buzzard. (2017) Convergence of Griddy Gibbs sampling and other perturbed Markov chains. Journal of Statistical Computation and Simulation 87:7, pages 1379-1400.
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Issac Shams, Saeede Ajorlou & Kai Yang. (2015) Bayesian component selection in multi-response hierarchical structured additive models with an application to clinical workload prediction in patient-centered medical homes. IIE Transactions 47:9, pages 943-960.
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Articles from other publishers (14)
David B. Huberman, Brian J. Reich & Howard D. Bondell. (2021) Nonparametric conditional density estimation in a deep learning framework for short-term forecasting. Environmental and Ecological Statistics 29:4, pages 677-704.
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Inkoo Lee, Debajyoti Sinha, Qing Mai, Xin Zhang & Dipankar Bandyopadhyay. (2022) Bayesian regression analysis of skewed tensor responses. Biometrics.
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Subharup Guha, Rex Jung & David Dunson. (2022) Predicting Phenotypes from Brain Connection Structure. Journal of the Royal Statistical Society Series C: Applied Statistics 71:3, pages 639-668.
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Minerva Mukhopadhyay & Sourabh Bhattacharya. (2021) Bayes factor asymptotics for variable selection in the Gaussian process framework. Annals of the Institute of Statistical Mathematics 74:3, pages 581-613.
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Xuerui Li, Lican Kang, Yanyan Liu & Yuanshan Wu. (2022) Distributed Bayesian posterior voting strategy for massive data. Electronic Research Archive 30:5, pages 1936-1953.
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Nadja Klein & Michael Stanley Smith. (2020) Bayesian variable selection for non‐Gaussian responses: a marginally calibrated copula approach. Biometrics 77:3, pages 809-823.
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Nadja Klein, Manuel Carlan, Thomas Kneib, Stefan Lang & Helga Wagner. (2021) Bayesian Effect Selection in Structured Additive Distributional Regression Models. Bayesian Analysis 16:2.
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Minwoo Chae, Lizhen Lin & David B Dunson. (2019) Bayesian sparse linear regression with unknown symmetric error. Information and Inference: A Journal of the IMA 8:3, pages 621-653.
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Suprateek Kundu, Bani K. Mallick & Veera Baladandayuthapani. (2019) Efficient Bayesian Regularization for Graphical Model Selection. Bayesian Analysis 14:2.
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Suprateek Kundu & Shan Suthaharan. (2019) Privacy-Preserving Predictive Model Using Factor Analysis for Neuroscience Applications. Privacy-Preserving Predictive Model Using Factor Analysis for Neuroscience Applications.
Subharup Guha & Veerabhadran Baladandayuthapani. (2016) A nonparametric Bayesian technique for high-dimensional regression. Electronic Journal of Statistics 10:2.
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Gertraud Malsiner-Walli, Sylvia Frühwirth-Schnatter & Bettina Grün. (2014) Model-based clustering based on sparse finite Gaussian mixtures. Statistics and Computing 26:1-2, pages 303-324.
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Qifan Song & Faming Liang. (2015) A Split-and-Merge Bayesian Variable Selection Approach for Ultrahigh Dimensional Regression. Journal of the Royal Statistical Society Series B: Statistical Methodology 77:5, pages 947-972.
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Heesang Noh, Jinsu Park, Gyuseok Sim, Jae-Eun Yu & Yeonseung Chung. (2014) Nonparametric Bayesian Statistical Models in Biomedical Research. Korean Journal of Applied Statistics 27:6, pages 867-889.
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