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Efficient Bayesian Regularization for Graphical Model Selection

There has been an intense development in the Bayesian graphical model literature over the past decade; however, most of the existing methods are restricted to moderate dimensions. We propose a novel graphical model selection approach for large dimensional settings where the dimension increases with...

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Bibliographische Detailangaben
Veröffentlicht in:Bayesian Anal
Hauptverfasser: Kundu, Suprateek, Mallick, Bani K., Baladandayuthapan, Veera
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2018
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7592715/
https://ncbi.nlm.nih.gov/pubmed/33123305
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/17-ba1086
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