The Bayesian Covariance Lasso.
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Hongtu Zhu | Joseph G Ibrahim | Weili Lin | Haitao Chu | H. Chu | J. Ibrahim | Weili Lin | Hongtu Zhu | Z. Khondker | Zakaria S Khondker
[1] Dinggang Shen,et al. Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects , 2009, Proceedings of the National Academy of Sciences.
[2] M. West,et al. Sparse graphical models for exploring gene expression data , 2004 .
[3] Xiao-Li Meng,et al. Modeling covariance matrices in terms of standard deviations and correlations, with application to shrinkage , 2000 .
[4] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[5] G. Casella,et al. The Bayesian Lasso , 2008 .
[6] Adam J. Rothman,et al. Sparse permutation invariant covariance estimation , 2008, 0801.4837.
[7] D. Dunson,et al. Random Effects Selection in Linear Mixed Models , 2003, Biometrics.
[8] Jun S. Liu,et al. The Multiple-Try Method and Local Optimization in Metropolis Sampling , 2000 .
[9] M. Yuan,et al. Model selection and estimation in the Gaussian graphical model , 2007 .
[10] D. Paul. ASYMPTOTICS OF SAMPLE EIGENSTRUCTURE FOR A LARGE DIMENSIONAL SPIKED COVARIANCE MODEL , 2007 .
[11] Sylvia Frühwirth-Schnatter,et al. Bayesian parsimonious covariance estimation for hierarchical linear mixed models , 2008, Stat. Comput..
[12] James G. Scott,et al. Feature-Inclusion Stochastic Search for Gaussian Graphical Models , 2008 .
[13] James G. Scott,et al. Objective Bayesian model selection in Gaussian graphical models , 2009 .
[14] M. Pourahmadi. Maximum likelihood estimation of generalised linear models for multivariate normal covariance matrix , 2000 .
[15] J. Berger,et al. Estimation of a Covariance Matrix Using the Reference Prior , 1994 .
[16] E. Davidson,et al. Gene regulatory networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.
[17] Jianhua Z. Huang,et al. Covariance matrix selection and estimation via penalised normal likelihood , 2006 .
[18] R. Christensen. Introduction to Graphical Modeling , 2001 .
[19] K. Sachs,et al. Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data , 2005, Science.
[20] H. Massam,et al. FLEXIBLE COVARIANCE ESTIMATION IN GRAPHICAL , 2008 .
[21] R. Kohn,et al. Efficient estimation of covariance selection models , 2003 .
[22] L. R. Haff. Minimax estimators for a multinormal precision matrix , 1977 .
[23] Y. Escoufier. LE TRAITEMENT DES VARIABLES VECTORIELLES , 1973 .
[24] Alexandre d'Aspremont,et al. Model Selection Through Sparse Maximum Likelihood Estimation , 2007, ArXiv.
[25] R. Kohn,et al. Parsimonious Covariance Matrix Estimation for Longitudinal Data , 2002 .
[26] M. Drton,et al. Model selection for Gaussian concentration graphs , 2004 .
[27] Jianqing Fan,et al. NETWORK EXPLORATION VIA THE ADAPTIVE LASSO AND SCAD PENALTIES. , 2009, The annals of applied statistics.
[28] K. Strimmer,et al. Statistical Applications in Genetics and Molecular Biology A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics , 2011 .