Bayesian inference for low-rank Ising networks

Estimating the structure of Ising networks is a notoriously difficult problem. We demonstrate that using a latent variable representation of the Ising network, we can employ a full-data-information approach to uncover the network structure. Thereby, only ignoring information encoded in the prior dis...

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Detalles Bibliográficos
Autores principales: Marsman, Maarten, Maris, Gunter, Bechger, Timo, Glas, Cees
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4356966/
https://www.ncbi.nlm.nih.gov/pubmed/25761415
http://dx.doi.org/10.1038/srep09050

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4356966/
https://www.ncbi.nlm.nih.gov/pubmed/25761415
http://dx.doi.org/10.1038/srep09050

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