Bayesian Analysis

Rejoinder

Marco Scutari

Full-text: Open access

Article information

Source
Bayesian Anal. Volume 8, Number 3 (2013), 549-552.

Dates
First available in Project Euclid: 9 September 2013

Permanent link to this document
https://projecteuclid.org/euclid.ba/1378729918

Digital Object Identifier
doi:10.1214/13-BA845

Mathematical Reviews number (MathSciNet)
MR3102224

Zentralblatt MATH identifier
1329.62146

Citation

Scutari, Marco. Rejoinder. Bayesian Anal. 8 (2013), no. 3, 549--552. doi:10.1214/13-BA845. https://projecteuclid.org/euclid.ba/1378729918.


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References

  • Aliferis, C. F., Statnikov, A., Tsamardinos, I., Mani, S., and Xenofon, X. D. (2010). “Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation.” Journal of Machine Learning Research, 11: 171–234.
  • Cai, T., Liu, W., and Luo, X. (2011). “A Constrained l1 Minimization Approach to Sparse Precision Matrix Estimation.” Journal of the American Statistical Association, 106(494): 594–607.
  • Friedman, N. and Koller, D. (2003). “Being Bayesian about Bayesian Network Structure: A Bayesian Approach to Structure Discovery in Bayesian Networks.” Machine Learning, 50(1–2): 95–126.
  • Ide, J. S. and Cozman, F. G. (2002). “Random Generation of Bayesian Networks.” In Proceedings of the 16th Brazilian Symposium on Artificial Intelligence, 366–375. Springer-Verlag.
  • Ide, J. S., Cozman, F. G., and Ramos, F. T. (2004). “Generating Random Bayesian Networks with Constraints on Induced Width.” In Proceedings of the 16th European Conference on Artificial Intelligence, 323–327. IOS Press.
  • Imoto, S., Higuchi, T., Goto, T., Tashiro, K., Kuhara, S., and Miyano, S. (2003). “Combining Microarrays and Biological Knowledge for Estimating Gene Networks via Bayesian Networks.” In Proceedings of the IEEE Computer Society Bioinformatics Conference, 104–113.
  • Ledoit, O. and Wolf, M. (2003). “Improved Estimation of the Covariance Matrix of Stock Returns with an Application to Portfolio Selection.” Journal of Empirical Finance, 10: 603–621.
  • Melançon, G., Dutour, I., and Bousquet-Mélou, M. (2000). “Random Generation of DAGs for Graph Drawing.” Technical Report INS-R0005, Centre for Mathematics and Computer Sciences, Amsterdam.
  • Mukherjee, S. and Speed, T. P. (2008). “Network inference using informative priors.” Proceedings of the National Academy of Sciences, 105(38): 14313–14318.
  • Sachs, K., Perez, O., Pe’er, D., Lauffenburger, D. A., and Nolan, G. P. (2005). “Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data.” Science, 308(5721): 523–529.
  • Schäfer, J. and Strimmer, K. (2005). “A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics.” Statistical Applications in Genetics and Molecular Biology, 4(32): 1175–1189.
  • Scutari, M. (2011). “Structure Variability in Bayesian Networks.” Ph.D. thesis, Department of Statistical Sciences, University of Padova.
  • Werhli, A. V. and Husmeier, D. (2007). “Reconstructing Gene Regulatory Networks with Bayesian Networks by Combining Expression Data with Multiple Sources of Prior Knowledge.” Statistical Applications in Genetics and Molecular Biology, 6(1): 1–45.

See also

  • Related item: Marco Scutari (2013). On the Prior and Posterior Distributions Used in Graphical Modelling. Bayesian Anal. Vol. 8, Iss. 3, 505–532.