Graphical modeling of binary data using the LASSO: a simulation study
暂无分享,去创建一个
[1] N. Meinshausen,et al. High-dimensional graphs and variable selection with the Lasso , 2006, math/0608017.
[2] Christophe Ambroise,et al. Inferring sparse Gaussian graphical models with latent structure , 2008, 0810.3177.
[3] A. Agresti. Categorical data analysis , 1993 .
[4] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[5] C. Camargo,et al. Methodological considerations, such as directed acyclic graphs, for studying "acute on chronic" disease epidemiology: chronic obstructive pulmonary disease example. , 2009, Journal of clinical epidemiology.
[6] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[7] R. Tibshirani,et al. Regression shrinkage and selection via the lasso: a retrospective , 2011 .
[8] N. Meinshausen,et al. Stability selection , 2008, 0809.2932.
[9] Tso-Jung Yen,et al. Discussion on "Stability Selection" by Meinshausen and Buhlmann , 2010 .
[10] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[11] L. Breiman. Heuristics of instability and stabilization in model selection , 1996 .
[12] M. Yuan,et al. Model selection and estimation in the Gaussian graphical model , 2007 .
[13] Eric Jougla,et al. An empirical comparative study of approximate methods for binary graphical models; application to the search of associations among causes of death in French death certificates , 2010, 1004.2287.
[14] H Nazirah,et al. THE APPLICATIONS OF INTERNATIONAL CLASSIFICATION OF FUNCTIONING, DISABILITY AND HEALTH (ICF) BY WORLD HEALTH ORGANIZATION(WHO) IN REHABILITATION MEDICINE PRACTICE , 2007 .
[15] Adam J. Rothman,et al. Sparse permutation invariant covariance estimation , 2008, 0801.4837.
[16] Alexandre d'Aspremont,et al. Model Selection Through Sparse Max Likelihood Estimation Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data , 2022 .
[17] Martin J. Wainwright,et al. High-Dimensional Graphical Model Selection Using ℓ1-Regularized Logistic Regression , 2006, NIPS.
[18] Yuehua Wu,et al. Tuning parameter selection for penalized likelihood estimation of inverse covariance matrix , 2009 .
[19] P. Bühlmann,et al. Statistical Applications in Genetics and Molecular Biology Low-Order Conditional Independence Graphs for Inferring Genetic Networks , 2011 .
[20] R. Kohn,et al. Efficient estimation of covariance selection models , 2003 .
[21] David Madigan,et al. Large-Scale Bayesian Logistic Regression for Text Categorization , 2007, Technometrics.
[22] J. Robins,et al. Instruments for Causal Inference: An Epidemiologist's Dream? , 2006, Epidemiology.
[23] S. Sathiya Keerthi,et al. A simple and efficient algorithm for gene selection using sparse logistic regression , 2003, Bioinform..
[24] Pei Wang,et al. Learning networks from high dimensional binary data: An application to genomic instability data , 2009, 0908.3882.
[25] R. Tibshirani. The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.
[26] J. Lafferty,et al. High-dimensional Ising model selection using ℓ1-regularized logistic regression , 2010, 1010.0311.
[27] R. Strobl,et al. Graphical modeling can be used to illustrate associations between variables describing functioning in head and neck cancer patients. , 2011, Journal of clinical epidemiology.
[28] Lawrence Carin,et al. Sparse multinomial logistic regression: fast algorithms and generalization bounds , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[29] C. S. Yost. Acute on Chronic , 2013 .
[30] D. Edwards. Introduction to graphical modelling , 1995 .
[31] F. Bunea. Honest variable selection in linear and logistic regression models via $\ell_1$ and $\ell_1+\ell_2$ penalization , 2008, 0808.4051.
[32] Francis R. Bach,et al. Bolasso: model consistent Lasso estimation through the bootstrap , 2008, ICML '08.
[33] M. T. J. Buñuales,et al. La clasificación internacional del funcionamiento de la discapacidad y de la salud (CIF) 2001 , 2002 .
[34] S. Geer. HIGH-DIMENSIONAL GENERALIZED LINEAR MODELS AND THE LASSO , 2008, 0804.0703.
[35] J. Goeman. L1 Penalized Estimation in the Cox Proportional Hazards Model , 2009, Biometrical journal. Biometrische Zeitschrift.
[36] Ulrich Mansmann,et al. Graphical models illustrated complex associations between variables describing human functioning. , 2009, Journal of clinical epidemiology.
[37] Peter Bühlmann,et al. Understanding human functioning using graphical models , 2010, BMC medical research methodology.
[38] Christian P. Robert,et al. Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.