Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis
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- Leonardo Bottolo & Marco Banterle & Sylvia Richardson & Mika Ala‐Korpela & Marjo‐Riitta Järvelin & Alex Lewin, 2021. "A computationally efficient Bayesian seemingly unrelated regressions model for high‐dimensional quantitative trait loci discovery," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(4), pages 886-908, August.
- Yang Ni & Veerabhadran Baladandayuthapani & Marina Vannucci & Francesco C. Stingo, 2022. "Bayesian graphical models for modern biological applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 197-225, June.
- Bai, Ray & Ghosh, Malay, 2018. "High-dimensional multivariate posterior consistency under global–local shrinkage priors," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 157-170.
- Federico Castelletti, 2020. "Bayesian Model Selection of Gaussian Directed Acyclic Graph Structures," International Statistical Review, International Statistical Institute, vol. 88(3), pages 752-775, December.
- Anindya Bhadra & Arvind Rao & Veerabhadran Baladandayuthapani, 2018. "Inferring network structure in non†normal and mixed discrete†continuous genomic data," Biometrics, The International Biometric Society, vol. 74(1), pages 185-195, March.
- Cao Xuan & Ding Lili & Mersha Tesfaye B., 2020. "Joint variable selection and network modeling for detecting eQTLs," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 19(1), pages 1-15, February.
- Li, Yunfan & Datta, Jyotishka & Craig, Bruce A. & Bhadra, Anindya, 2021. "Joint mean–covariance estimation via the horseshoe," Journal of Multivariate Analysis, Elsevier, vol. 183(C).
- Nikolaos Petrakis & Stefano Peluso & Dimitris Fouskakis & Guido Consonni, 2020. "Objective methods for graphical structural learning," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 420-438, August.
- Codazzi, Laura & Colombi, Alessandro & Gianella, Matteo & Argiento, Raffaele & Paci, Lucia & Pini, Alessia, 2022. "Gaussian graphical modeling for spectrometric data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
- Anindya Bhadra & Jyotishka Datta & Yunfan Li & Nicholas Polson, 2020. "Horseshoe Regularisation for Machine Learning in Complex and Deep Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 302-320, August.
- Federico Castelletti & Guido Consonni & Luca Rocca, 2022. "Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 261-267, June.
- Guido Consonni & Luca La Rocca & Stefano Peluso, 2017. "Objective Bayes Covariate-Adjusted Sparse Graphical Model Selection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 741-764, September.
- Paci, Lucia & Consonni, Guido, 2020. "Structural learning of contemporaneous dependencies in graphical VAR models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
- Runmin Shi & Faming Liang & Qifan Song & Ye Luo & Malay Ghosh, 2018. "A Blockwise Consistency Method for Parameter Estimation of Complex Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 179-223, December.
- Marco Molinari & Andrea Cremaschi & Maria De Iorio & Nishi Chaturvedi & Alun D. Hughes & Therese Tillin, 2022. "Bayesian nonparametric modelling of multiple graphs with an application to ethnic metabolic differences," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1181-1204, November.
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