References
- Akaike, H. (1998). Information theory and an extension of the maximum likelihood principle. In: Parzen, E., Tanabe, K., Kitagawa, G. Selected Papers of Hirotugu Akaike. New York: Springer, pp. 199–213.
- Cai, T. T., Liu, W., Luo, X. (2011). A constrained ℓ1 minimization approach for sparse precision matrix estimation. Journal of the American Statistical Association 106(494):594–607.
- Efron, B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans. Vol. 38. Philadelphia, PA: Society for Industrial and Applied Mathematics.
- Fraley, C., Percival, D. (2013). Model-averaged ℓ1 regularization using Markov chain Monte Carlo model composition. Journal of Statistical Computation and Simulation 85(6):1090–1101.
- Friedman, J., Hastie, T., Tibshirani, R. (2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics 9(3):432–441.
- Hastie, T., Friedman, J., Tibshirani, R. (2009). The Elements of Statistical Learning. New York: Springer.
- Hoeting, J. A., Madigan, D., Raftery, A. E., Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science 14(4):382–417.
- Lauritzen, S. L. (1996). Graphical Models. New York: Oxford University Press.
- Leung, G., Barron, A. R. (2006). Information theory and mixing least-squares regressions. IEEE Transactions on Information Theory 52(8):3396–3410.
- Liu, H., Roeder, K., Wasserman, L. (2010). Stability approach to regularization selection (StARS) for high dimensional graphical models. Advances in Neural Information Processing Systems 23:1432–1440.
- Nayak, R. R., Kearns, M., Spielman, R. S., Cheung, V. G. (2009). Coexpression network based on natural variation in human gene expression reveals gene interactions and functions. Genome Research 19(11):1953–1962.
- Raftery, A. E. (1995). Bayesian model selection in social research. Sociological Methodology 25:111–164.
- Raskutti, G., Yu, B., Wainwright, M. J., Ravikumar, P. K. (2008). Model selection in Gaussian graphical models: High-dimensional consistency of ℓ1-regularized MLE. Advances in Neural Information Processing Systems 21:1329–1336.
- Rigollet, P., Tsybakov, A. (2011). Exponential screening and optimal rates of sparse estimation. The Annals of Statistics 39(2):731–771.
- Rigollet, P., Tsybakov, A. B. (2012). Sparse estimation by exponential weighting. Statistical Science 27(4):558–575.
- Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics 6(2):461–464.
- Uhler, C. (2012). Geometry of maximum likelihood estimation in Gaussian graphical models. The Annals of Statistics 40(1):238–261.
- Whittaker, J. (2009). Graphical Models in Applied Multivariate Statistics. New York: Wiley Publishing.
- Yuan, M., Lin, Y. (2007). Model selection and estimation in the Gaussian graphical model. Biometrika 94(1):19–35.
- Zhao, T., Liu, H., Roeder, K., Lafferty, J., Wasserman, L. (2012). The huge package for high-dimensional undirected graph estimation in R. The Journal of Machine Learning Research 13(1):1059–1062.