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Bayesian graph selection consistency under model misspecification

Gaussian graphical models are a popular tool to learn the dependence structure in the form of a graph among variables of interest. Bayesian methods have gained in popularity in the last two decades due to their ability to simultaneously learn the covariance and the graph. There is a wide variety of...

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Bibliographische Detailangaben
Veröffentlicht in:Bernoulli (Andover)
Hauptverfasser: NIU, YABO, PATI, DEBDEEP, MALLICK, BANI K.
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2020
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC8300537/
https://ncbi.nlm.nih.gov/pubmed/34305432
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3150/20-BEJ1253
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