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The joint graphical lasso for inverse covariance estimation across multiple classes

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Cited by:

  1. Azam Kheyri & Andriette Bekker & Mohammad Arashi, 2022. "High-Dimensional Precision Matrix Estimation through GSOS with Application in the Foreign Exchange Market," Mathematics, MDPI, vol. 10(22), pages 1-19, November.
  2. Wang, Ke & Franks, Alexander & Oh, Sang-Yun, 2023. "Learning Gaussian graphical models with latent confounders," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  3. Pircalabelu, Eugen, 2022. "WB-graphs: a within versus between group similarity interplay," LIDAM Discussion Papers ISBA 2022007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  4. van Wieringen, Wessel N. & Stam, Koen A. & Peeters, Carel F.W. & van de Wiel, Mark A., 2020. "Updating of the Gaussian graphical model through targeted penalized estimation," Journal of Multivariate Analysis, Elsevier, vol. 178(C).
  5. Saverio Ranciati & Alberto Roverato & Alessandra Luati, 2021. "Fused graphical lasso for brain networks with symmetries," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(5), pages 1299-1322, November.
  6. Maxwell P. Gold & Winnie Ong & Andrew M. Masteller & David R. Ghasemi & Julie Anne Galindo & Noel R. Park & Nhan C. Huynh & Aneesh Donde & Veronika Pister & Raul A. Saurez & Maria C. Vladoiu & Grace H, 2024. "Developmental basis of SHH medulloblastoma heterogeneity," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
  7. A. Bekker & A. Kheyri & M. Arashi, 2026. "Augmented Graphical Ridge Estimation with Application in the Cryptocurrency Market," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 781-825, February.
  8. Barbaglia, Luca & Wilms, Ines & Croux, Christophe, 2016. "Commodity dynamics: A sparse multi-class approach," Energy Economics, Elsevier, vol. 60(C), pages 62-72.
  9. Zongliang Hu & Zhishui Hu & Kai Dong & Tiejun Tong & Yuedong Wang, 2021. "A shrinkage approach to joint estimation of multiple covariance matrices," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(3), pages 339-374, April.
  10. Zhang, Qihu & Chung, Jongik & Park, Cheolwoo, 2025. "Joint estimation of precision matrices for long-memory time series," Computational Statistics & Data Analysis, Elsevier, vol. 212(C).
  11. Yin Xia & Lexin Li, 2017. "Hypothesis testing of matrix graph model with application to brain connectivity analysis," Biometrics, The International Biometric Society, vol. 73(3), pages 780-791, September.
  12. Masashi Hyodo & Nobumichi Shutoh & Takahiro Nishiyama & Tatjana Pavlenko, 2015. "Testing block-diagonal covariance structure for high-dimensional data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(4), pages 460-482, November.
  13. Elin Shaddox & Francesco C. Stingo & Christine B. Peterson & Sean Jacobson & Charmion Cruickshank-Quinn & Katerina Kechris & Russell Bowler & Marina Vannucci, 2018. "A Bayesian Approach for Learning Gene Networks Underlying Disease Severity in COPD," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(1), pages 59-85, April.
  14. Li, Lijie & Yu, Yang & Liang, Wanfeng & Zou, Feng, 2025. "A novel approach for estimating multi-attribute Gaussian copula graphical models," Statistics & Probability Letters, Elsevier, vol. 222(C).
  15. Mingyang Ren & Sanguo Zhang & Qingzhao Zhang & Shuangge Ma, 2022. "Gaussian graphical model‐based heterogeneity analysis via penalized fusion," Biometrics, The International Biometric Society, vol. 78(2), pages 524-535, June.
  16. Zhixiang Lin & Tao Wang & Can Yang & Hongyu Zhao, 2017. "On joint estimation of Gaussian graphical models for spatial and temporal data," Biometrics, The International Biometric Society, vol. 73(3), pages 769-779, September.
  17. Dong, Wei & Xu, Chen & Xie, Jinhan & Tang, Niansheng, 2024. "Tuning-free sparse clustering via alternating hard-thresholding," Journal of Multivariate Analysis, Elsevier, vol. 203(C).
  18. Jos'e Vin'icius de Miranda Cardoso & Jiaxi Ying & Daniel Perez Palomar, 2020. "Algorithms for Learning Graphs in Financial Markets," Papers 2012.15410, arXiv.org.
  19. Skripnikov, A. & Michailidis, G., 2019. "Regularized joint estimation of related vector autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 164-177.
  20. Jonathan Tuck & Shane Barratt & Stephen Boyd, 2021. "Portfolio Construction Using Stratified Models," Papers 2101.04113, arXiv.org, revised Feb 2021.
  21. Banerjee, Sayantan, 2022. "Horseshoe shrinkage methods for Bayesian fusion estimation," Computational Statistics & Data Analysis, Elsevier, vol. 174(C).
  22. Li‐Pang Chen, 2024. "Estimation of Graphical Models: An Overview of Selected Topics," International Statistical Review, International Statistical Institute, vol. 92(2), pages 194-245, August.
  23. Beatrice Franzolini & Alexandros Beskos & Maria De Iorio & Warrick Poklewski Koziell & Karolina Grzeszkiewicz, 2022. "Change point detection in dynamic Gaussian graphical models: the impact of COVID-19 pandemic on the US stock market," Papers 2208.00952, arXiv.org, revised May 2023.
  24. Jianyu Liu & Wei Sun & Yufeng Liu, 2019. "Joint skeleton estimation of multiple directed acyclic graphs for heterogeneous population," Biometrics, The International Biometric Society, vol. 75(1), pages 36-47, March.
  25. Young-Geun Choi & Seunghwan Lee & Donghyeon Yu, 2022. "An efficient parallel block coordinate descent algorithm for large-scale precision matrix estimation using graphics processing units," Computational Statistics, Springer, vol. 37(1), pages 419-443, March.
  26. Hristina Pashova & Michael LeBlanc & Charles Kooperberg, 2017. "Structured Detection of Interactions with the Directed Lasso," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 676-691, December.
  27. Gaynanova, Irina & Wang, Tianying, 2019. "Sparse quadratic classification rules via linear dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 278-299.
  28. Sai Li & T. Tony Cai & Hongzhe Li, 2022. "Transfer learning for high‐dimensional linear regression: Prediction, estimation and minimax optimality," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 149-173, February.
  29. Jie Jian & Peijun Sang & Mu Zhu, 2024. "Two Gaussian Regularization Methods for Time-Varying Networks," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(4), pages 853-873, December.
  30. Conte, Federica & Costantini, Giulio & Rinaldi, Luca & Gerosa, Tiziano & Girelli, Luisa, 2020. "Intellect is not that expensive: differential association of cultural and socio-economic factors with crystallized intelligence in a sample of Italian adolescents," Intelligence, Elsevier, vol. 81(C).
  31. Yang Ni & Peter Müller & Yitan Zhu & Yuan Ji, 2018. "Heterogeneous reciprocal graphical models," Biometrics, The International Biometric Society, vol. 74(2), pages 606-615, June.
  32. Hyungrok Do & Shinjini Nandi & Preston Putzel & Padhraic Smyth & Judy Zhong, 2023. "A joint fairness model with applications to risk predictions for underrepresented populations," Biometrics, The International Biometric Society, vol. 79(2), pages 826-840, June.
  33. Claudia Angelini & Daniela De Canditiis & Anna Plaksienko, 2021. "Jewel : A Novel Method for Joint Estimation of Gaussian Graphical Models," Mathematics, MDPI, vol. 9(17), pages 1-24, August.
  34. Dong Liu & Changwei Zhao & Yong He & Lei Liu & Ying Guo & Xinsheng Zhang, 2023. "Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix‐variate fMRI data," Biometrics, The International Biometric Society, vol. 79(3), pages 2246-2259, September.
  35. Mehran Aflakparast & Mathisca de Gunst & Wessel van Wieringen, 2020. "Analysis of Twitter data with the Bayesian fused graphical lasso," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-28, July.
  36. Yize Zhao & Zhe Sun & Jian Kang, 2022. "Discussion to: Bayesian graphical models for modern biological applications by Y. Ni, V. Baladandayuthapani, M. Vannucci and F.C. Stingo," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 279-286, June.
  37. Alessandro Casa & Andrea Cappozzo & Michael Fop, 2022. "Group-Wise Shrinkage Estimation in Penalized Model-Based Clustering," Journal of Classification, Springer;The Classification Society, vol. 39(3), pages 648-674, November.
  38. Marco Molinari & Andrea Cremaschi & Maria De Iorio & Nishi Chaturvedi & Alun D. Hughes & Therese Tillin, 2022. "Bayesian nonparametric modelling of multiple graphs with an application to ethnic metabolic differences," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1181-1204, November.
  39. Lee, Kyoungjae & Cao, Xuan, 2022. "Bayesian joint inference for multiple directed acyclic graphs," Journal of Multivariate Analysis, Elsevier, vol. 191(C).
  40. Aaron Hudson & Ali Shojaie, 2022. "Covariate-Adjusted Inference for Differential Analysis of High-Dimensional Networks," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 345-388, June.
  41. Fan, Xinyan & Zhang, Qingzhao & Ma, Shuangge & Fang, Kuangnan, 2021. "Conditional score matching for high-dimensional partial graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
  42. Kevin H. Lee & Qian Chen & Wayne S. DeSarbo & Lingzhou Xue, 2022. "Estimating Finite Mixtures of Ordinal Graphical Models," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 83-106, March.
  43. Zhang, Qingzhao & Ma, Shuangge & Huang, Yuan, 2021. "Promote sign consistency in the joint estimation of precision matrices," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
  44. Pircalabelu, Eugen & Artemiou, Andreas, 2021. "Graph informed sliced inverse regression," Computational Statistics & Data Analysis, Elsevier, vol. 164(C).
  45. Shane Barratt & Stephen Boyd, 2020. "Multi-Period Liability Clearing via Convex Optimal Control," Papers 2005.09066, arXiv.org.
  46. Yang Ni & Veerabhadran Baladandayuthapani & Marina Vannucci & Francesco C. Stingo, 2022. "Bayesian graphical models for modern biological applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(2), pages 197-225, June.
  47. Zhu, Xiaonan & Chen, Yu & Hu, Jie, 2024. "Estimation of banded time-varying precision matrix based on SCAD and group lasso," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
  48. Bernadin Namoano & Christina Latsou & John Ahmet Erkoyuncu, 2025. "Multi-channel anomaly detection using graphical models," Journal of Intelligent Manufacturing, Springer, vol. 36(6), pages 4319-4330, August.
  49. Junghi Kim & Kim‐Anh Do & Min Jin Ha & Christine B. Peterson, 2019. "Bayesian inference of hub nodes across multiple networks," Biometrics, The International Biometric Society, vol. 75(1), pages 172-182, March.
  50. Christine B. Peterson & Nathan Osborne & Francesco C. Stingo & Pierrick Bourgeat & James D. Doecke & Marina Vannucci, 2020. "Bayesian modeling of multiple structural connectivity networks during the progression of Alzheimer's disease," Biometrics, The International Biometric Society, vol. 76(4), pages 1120-1132, December.
  51. He, Yong & Zhang, Xinsheng & Wang, Pingping, 2016. "Discriminant analysis on high dimensional Gaussian copula model," Statistics & Probability Letters, Elsevier, vol. 117(C), pages 100-112.
  52. Wessel N. van Wieringen & Carel F. W. Peeters & Renee X. de Menezes & Mark A. van de Wiel, 2018. "Testing for pathway (in)activation by using Gaussian graphical models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1419-1436, November.
  53. Jiaqi Zhang & Xinyan Fan & Yang Li & Shuangge Ma, 2022. "Heterogeneous graphical model for non‐negative and non‐Gaussian PM2.5 data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1303-1329, November.
  54. Qin, Xing & Hu, Jianhua & Ma, Shuangge & Wu, Mengyun, 2024. "Estimation of multiple networks with common structures in heterogeneous subgroups," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
  55. Huitong Qiu & Fang Han & Han Liu & Brian Caffo, 2016. "Joint estimation of multiple graphical models from high dimensional time series," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 487-504, March.
  56. Pircalabelu, Eugen & Claeskens, Gerda, 2021. "Linear manifold modeling and graph estimation based on multivariate functional data with different coarseness scales," LIDAM Discussion Papers ISBA 2021032, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  57. Zhou, Jia & Li, Yang & Zheng, Zemin & Li, Daoji, 2022. "Reproducible learning in large-scale graphical models," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
  58. Hoai An Le Thi & Tao Pham Dinh, 2024. "Open issues and recent advances in DC programming and DCA," Journal of Global Optimization, Springer, vol. 88(3), pages 533-590, March.
  59. Emma Pierson & the GTEx Consortium & Daphne Koller & Alexis Battle & Sara Mostafavi, 2015. "Sharing and Specificity of Co-expression Networks across 35 Human Tissues," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-19, May.
  60. Shanghong Xie & Xiang Li & Peter McColgan & Rachael I. Scahill & Donglin Zeng & Yuanjia Wang, 2020. "Identifying disease‐associated biomarker network features through conditional graphical model," Biometrics, The International Biometric Society, vol. 76(3), pages 995-1006, September.
  61. Byol Kim & Song Liu & Mladen Kolar, 2021. "Two‐sample inference for high‐dimensional Markov networks," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 939-962, November.
  62. Zhiguang Huo & Li Zhu & Tianzhou Ma & Hongcheng Liu & Song Han & Daiqing Liao & Jinying Zhao & George Tseng, 2020. "Two-Way Horizontal and Vertical Omics Integration for Disease Subtype Discovery," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(1), pages 1-22, April.
  63. Chen, Xin & Yang, Dan & Xu, Yan & Xia, Yin & Wang, Dong & Shen, Haipeng, 2023. "Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data," Journal of Econometrics, Elsevier, vol. 232(2), pages 544-564.
  64. Shuichi Kawano, 2021. "Sparse principal component regression via singular value decomposition approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 795-823, September.
  65. Li, Peili & Xiao, Yunhai, 2018. "An efficient algorithm for sparse inverse covariance matrix estimation based on dual formulation," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 292-307.
  66. Qingyang Liu & Yuping Zhang, 2023. "Integrative Structural Learning of Mixed Graphical Models via Pseudo-likelihood," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(3), pages 562-582, December.
  67. Dallakyan, Aramayis & Kim, Rakheon & Pourahmadi, Mohsen, 2022. "Time series graphical lasso and sparse VAR estimation," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
  68. Lin Zhang & Andrew DiLernia & Karina Quevedo & Jazmin Camchong & Kelvin Lim & Wei Pan, 2021. "A random covariance model for bi‐level graphical modeling with application to resting‐state fMRI data," Biometrics, The International Biometric Society, vol. 77(4), pages 1385-1396, December.
  69. Meichen Dong & Yiping He & Yuchao Jiang & Fei Zou, 2023. "Joint gene network construction by single‐cell RNA sequencing data," Biometrics, The International Biometric Society, vol. 79(2), pages 915-925, June.
  70. Yize Zhao & Ben Wu & Jian Kang, 2023. "Bayesian interaction selection model for multimodal neuroimaging data analysis," Biometrics, The International Biometric Society, vol. 79(2), pages 655-668, June.
  71. Claudia Angelini & Daniela De Canditiis & Anna Plaksienko, 2022. "Jewel 2.0 : An Improved Joint Estimation Method for Multiple Gaussian Graphical Models," Mathematics, MDPI, vol. 10(21), pages 1-20, October.
  72. Shan, Liang & Kim, Inyoung, 2018. "Joint estimation of multiple Gaussian graphical models across unbalanced classes," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 89-103.
  73. Bin Guo & Song Xi Chen, 2016. "Tests for high dimensional generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(5), pages 1079-1102, November.
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