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The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes
Open accessAbstract
Summary: We consider the problem of estimating multiple related Gaussian graphical models from a high dimensional data set with observations belonging to distinct classes. We propose the joint graphical lasso, which borrows strength across the classes to estimate multiple graphical models that share certain characteristics, such as the locations or weights of non-zero edges. Our approach is based on maximizing a penalized log-likelihood. We employ generalized fused lasso or group lasso penalties and implement a fast alternating directions method of multipliers algorithm to solve the corresponding convex optimization problems. The performance of the method proposed is illustrated through simulated and real data examples.
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Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
Lauritzen, S. L. (1996) · doi:10.1093/oso/9780198522195.001.0001 · Cited by 2,976
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Metadata
- Authors
- Danaher, P., Wang, P., & Witten, D. M.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-08-12
- Volume
- 76
- Issue
- 2
- Pages
- 373-397
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2165009258
- Cited by
- 855
- References
- 4
- FWCI
- 45.88
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Danaher, P., Wang, P., & Witten, D. M. (2014). The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes. Journal of the Royal Statistical Society Series B: Statistical Methodology. https://doi.org/10.1111/rssb.12033
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