Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo

Author:

Castelletti FedericoORCID,Consonni Guido,La Rocca Luca

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Reference21 articles.

1. Altomare D, Consonni G, La Rocca L (2013) Objective Bayesian search of Gaussian directed acyclic graphical models for ordered variables with non-local priors. Biometrics 69(2):478–487

2. Andersson SA, Madigan D, Perlman MD (1997) A characterization of Markov equivalence classes for acyclic digraphs. Ann Stat 25(2):505–541

3. Argiento R, De Iorio M (2019) Is infinity that far? A Bayesian nonparametric perspective of finite mixture models. arXiv preprint arXiv:1904.09733, Cornell University

4. Ben-David E, Li T, Massam H, Rajaratnam B (2015) High dimensional Bayesian inference for Gaussian directed acyclic graph models. arXiv preprint arXiv:1109.4371, Cornell University

5. Bhadra A, Mallick B (2013) Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis. Biometrics 69(2):447–457

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