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Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data
We introduce efficient Markov chain Monte Carlo methods for inference and model determination in multivariate and matrix-variate Gaussian graphical models. Our framework is based on the G-Wishart prior for the precision matrix associated with graphs that can be decomposable or non-decomposable. We e...
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| Vydáno v: | J Am Stat Assoc |
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| Hlavní autoři: | , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2012
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4767185/ https://ncbi.nlm.nih.gov/pubmed/26924867 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1198/jasa.2011.tm10465 |
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