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Condition-number-regularized covariance estimation

Citations

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Cited by:

  1. Hannart, Alexis & Naveau, Philippe, 2014. "Estimating high dimensional covariance matrices: A new look at the Gaussian conjugate framework," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 149-162.
  2. Ding, Wenliang & Shu, Lianjie & Gu, Xinhua, 2023. "A robust Glasso approach to portfolio selection in high dimensions," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 22-37.
  3. 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.
  4. Morana, Claudio, 2019. "Regularized semiparametric estimation of high dimensional dynamic conditional covariance matrices," Econometrics and Statistics, Elsevier, vol. 12(C), pages 42-65.
  5. Lingxiao Huang & K. Sudhir & Nisheeth K. Vishnoi, 2021. "Coresets for Time Series Clustering," Papers 2110.15263, arXiv.org.
  6. Jianqing Fan & Yuan Liao & Martina Mincheva, 2013. "Large covariance estimation by thresholding principal orthogonal complements," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(4), pages 603-680, September.
  7. Brett Naul & Bala Rajaratnam & Dario Vincenzi, 2016. "The role of the isotonizing algorithm in Stein’s covariance matrix estimator," Computational Statistics, Springer, vol. 31(4), pages 1453-1476, December.
  8. Edoardo Di Porto & Angela Parenti & Sonia Paty & Zineb Abidi, 2017. "Local government cooperation at work: a control function approach," Journal of Economic Geography, Oxford University Press, vol. 17(2), pages 435-463.
  9. Seonghun Cho & Shota Katayama & Johan Lim & Young-Geun Choi, 2021. "Positive-definite modification of a covariance matrix by minimizing the matrix $$\ell_{\infty}$$ ℓ ∞ norm with applications to portfolio optimization," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 601-627, December.
  10. Lingxiao Huang & K. Sudhir & Nisheeth Vishnoi, 2021. "Coresets for Time Series Clustering," Cowles Foundation Discussion Papers 2310, Cowles Foundation for Research in Economics, Yale University.
  11. Kwon, Yongchan & Choi, Young-Geun & Park, Taesung & Ziegler, Andreas & Paik, Myunghee Cho, 2017. "Generalized estimating equations with stabilized working correlation structure," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 1-11.
  12. Wang, Shaoxin, 2021. "An efficient numerical method for condition number constrained covariance matrix approximation," Applied Mathematics and Computation, Elsevier, vol. 397(C).
  13. van Wieringen, Wessel N. & Peeters, Carel F.W., 2016. "Ridge estimation of inverse covariance matrices from high-dimensional data," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 284-303.
  14. Chi, Eric C. & Lange, Kenneth, 2014. "Stable estimation of a covariance matrix guided by nuclear norm penalties," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 117-128.
  15. Luger, Richard, 2025. "Regularizing stock return covariance matrices via multiple testing of correlations," Journal of Econometrics, Elsevier, vol. 248(C).
  16. Viet Anh Nguyen & Daniel Kuhn & Peyman Mohajerin Esfahani, 2018. "Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator," Papers 1805.07194, arXiv.org.
  17. Abadir, Karim M. & Distaso, Walter & Žikeš, Filip, 2014. "Design-free estimation of variance matrices," Journal of Econometrics, Elsevier, vol. 181(2), pages 165-180.
  18. Yu Li & Yuhan Wu & Shuhua Zhang, 2025. "The Exploratory Multi-Asset Mean-Variance Portfolio Selection using Reinforcement Learning," Papers 2505.07537, arXiv.org.
  19. Carel F. W. Peeters & Mark A. Wiel & Wessel N. Wieringen, 2020. "The spectral condition number plot for regularization parameter evaluation," Computational Statistics, Springer, vol. 35(2), pages 629-646, June.
  20. Gabriele Torri & Rosella Giacometti & Sandra Paterlini, 2019. "Sparse precision matrices for minimum variance portfolios," Computational Management Science, Springer, vol. 16(3), pages 375-400, July.
  21. Prateek Sharma & Vipul, 2018. "Improving portfolio diversification: Identifying the right baskets for putting your eggs," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 39(6), pages 698-711, September.
  22. 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.
  23. Choi, Young-Geun & Lim, Johan & Roy, Anindya & Park, Junyong, 2019. "Fixed support positive-definite modification of covariance matrix estimators via linear shrinkage," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 234-249.
  24. Lam, Clifford, 2020. "High-dimensional covariance matrix estimation," LSE Research Online Documents on Economics 101667, London School of Economics and Political Science, LSE Library.
  25. Soufiane Hayou, 2017. "On the overestimation of the largest eigenvalue of a covariance matrix," Papers 1708.03551, arXiv.org.
  26. Rajaratnam, Bala & Salzman, Julia, 2013. "Best permutation analysis," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 193-223.
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