# Plot function for S3 class "select"

### Description

Plot the optimal graph by model selection

### Usage

1 2 |

### Arguments

`x` |
An object with S3 class |

`...` |
System reserved (No specific usage) |

### Author(s)

Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, and Larry Wasserman

Maintainers: Tuo Zhao<tzhao5@jhu.edu>

### References

1. T. Zhao and H. Liu. The huge Package for High-dimensional Undirected Graph Estimation in R. *Journal of Machine Learning Research*, 2012

2. H. Liu, F. Han, M. Yuan, J. Lafferty and L. Wasserman. High Dimensional Semiparametric Gaussian Copula Graphical Models. *Annals of Statistics*,2012

3. D. Witten and J. Friedman. New insights and faster computations for the graphical lasso. *Journal of Computational and Graphical Statistics*, to appear, 2011.
4. Han Liu, Kathryn Roeder and Larry Wasserman. Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models. *Advances in Neural Information Processing Systems*, 2010.

5. R. Foygel and M. Drton. Extended bayesian information criteria for gaussian graphical models. *Advances in Neural Information Processing Systems*, 2010.

6. H. Liu, J. Lafferty and L. Wasserman. The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs. *Journal of Machine Learning Research*, 2009

7. J. Fan and J. Lv. Sure independence screening for ultra-high dimensional feature space (with discussion). *Journal of Royal Statistical Society B*, 2008.

8. O. Banerjee, L. E. Ghaoui, A. d'Aspremont: Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data. *Journal of Machine Learning Research*, 2008.

9. J. Friedman, T. Hastie and R. Tibshirani. Regularization Paths for Generalized Linear Models via Coordinate Descent. *Journal of Statistical Software*, 2008.

10. J. Friedman, T. Hastie and R. Tibshirani. Sparse inverse covariance estimation with the lasso, *Biostatistics*, 2007.

11. N. Meinshausen and P. Buhlmann. High-dimensional Graphs and Variable Selection with the Lasso. *The Annals of Statistics*, 2006.

### See Also

`huge.select`