Structural inference of time‐varying mixed graphical models
Author:
Affiliation:
1. Department of Statistics University of Connecticut Storrs CT 06269 USA
2. Department of Biostatistics and Epidemiology School of Public Health and Health Sciences, University of Massachusetts Amherst Amherst MA 01003 USA
Funder
Division of Mathematical Sciences
Publisher
Wiley
Subject
Statistics, Probability and Uncertainty,Statistics and Probability
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/sta4.414
Reference40 articles.
1. Allen G. I. &Liu Z.(2012).A log‐linear graphical model for inferring genetic networks from high‐throughput sequencing data. In2012 IEEE International Conference on Bioinformatics and Biomedicine pp.1–6.
2. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
3. Interaction networks: From protein functions to drug discovery. A review
4. Selection and estimation for mixed graphical models
5. High-Dimensional Mixed Graphical Models
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