Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison-Reference-Cited by-同舟云学术

Bayesian Structure Learning in Undirected Gaussian Graphical Models: Literature Review with Empirical Comparison

Published:2024-08-30 Issue: Volume: Page:1-33
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Vogels Lucas¹^ORCID,Mohammadi Reza¹^ORCID,Schoonhoven Marit¹,Birbil Ş. İlker¹

Affiliation:

1. Faculty of Economics and Business, University of Amsterdam

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2024.2395504

Reference100 articles.

1. Atay-Kayis A. and Massam H. (2005) ‘A Monte Carlo method for computing the marginal likelihood in non-decomposable Gaussian graphical models’ Biometrika 92(2) 317–335.

2. Atchadé Y. F. (2019) ‘Quasi-Bayesian estimation of large Gaussian graphical models’ Journal of Multivariate Analysis 173 656–671.

3. Banerjee O. El Ghaoui L. and d’Aspremont A. (2008) ‘Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data’ Journal of Machine Learning Research 9 485–516.

4. Besag J. (1975) ‘Statistical analysis of non-lattice data’ Journal of the Royal Statistical Society. Series D (The Statistician) 24(3) 179–195.

5. Bhadra A. and Mallick B. (2013) ‘Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis’ Biometrics 69 447–457.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Bayesian Scalable Precision Factor Analysis for Gaussian Graphical Models;Bayesian Analysis;2024-01-01