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Partial Correlation Estimation by Joint Sparse Regression Models

Author

Listed:
  • Peng, Jie
  • Wang, Pei
  • Zhou, Nengfeng
  • Zhu, Ji

Abstract

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Suggested Citation

  • Peng, Jie & Wang, Pei & Zhou, Nengfeng & Zhu, Ji, 2009. "Partial Correlation Estimation by Joint Sparse Regression Models," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 735-746.
  • Handle: RePEc:bes:jnlasa:v:104:i:486:y:2009:p:735-746
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    Cited by:

    1. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    2. Matteo Barigozzi & Christian Brownlees, 2013. "Nets: Network Estimation for Time Series," Working Papers 723, Barcelona Graduate School of Economics.
    3. Yin, Jianxin & Li, Hongzhe, 2013. "Adjusting for high-dimensional covariates in sparse precision matrix estimation by ℓ1-penalization," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 365-381.
    4. Natalia Bailey & M. Hashem Pesaran & L. Vanessa Smith, 2014. "A Multiple Testing Approach to the Regularisation of Large Sample Correlation Matrices," CESifo Working Paper Series 4834, CESifo Group Munich.
    5. Nogales Martín, Francisco Javier & Lafit, Ginette, 2017. "Robust and sparse estimation of high-dimensional precision matrices via bivariate outlier detection," DES - Working Papers. Statistics and Econometrics. WS 24534, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. 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.
    7. Hokeun Sun & Hongzhe Li, 2012. "Robust Gaussian Graphical Modeling Via l 1 Penalization," Biometrics, The International Biometric Society, vol. 68(4), pages 1197-1206, December.
    8. Zamar, Rubén & Nogales Martín, Francisco Javier & Lafit, Ginette, 2015. "Ranking Edges and Model Selection in High-Dimensional Graphs," DES - Working Papers. Statistics and Econometrics. WS ws1511, Universidad Carlos III de Madrid. Departamento de Estadística.
    9. repec:taf:gnstxx:v:29:y:2017:i:4:p:884-902 is not listed on IDEAS
    10. Tan, Kean Ming & Witten, Daniela & Shojaie, Ali, 2015. "The cluster graphical lasso for improved estimation of Gaussian graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 85(C), pages 23-36.
    11. Ambroise Jérôme & Robert Annie & Macq Benoit & Gala Jean-Luc, 2012. "Transcriptional Network Inference from Functional Similarity and Expression Data: A Global Supervised Approach," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-24, January.
    12. repec:bla:jorssb:v:79:y:2017:i:2:p:405-421 is not listed on IDEAS
    13. Luo, Shan & Chen, Zehua, 2014. "Edge detection in sparse Gaussian graphical models," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 138-152.
    14. Anindya Bhadra & Bani K. Mallick, 2013. "Joint High-Dimensional Bayesian Variable and Covariance Selection with an Application to eQTL Analysis," Biometrics, The International Biometric Society, vol. 69(2), pages 447-457, June.
    15. Kk{e}stutis Baltakys & Juho Kanniainen & Frank Emmert-Streib, 2017. "Multilayer Aggregation with Statistical Validation: Application to Investor Networks," Papers 1708.09850, arXiv.org, revised May 2018.
    16. Jie Cheng & Elizaveta Levina & Pei Wang & Ji Zhu, 2014. "A sparse ising model with covariates," Biometrics, The International Biometric Society, vol. 70(4), pages 943-953, December.
    17. Lee, Wonyul & Liu, Yufeng, 2012. "Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood," Journal of Multivariate Analysis, Elsevier, vol. 111(C), pages 241-255.
    18. Joong-Ho Won & Johan Lim & Seung-Jean Kim & Bala Rajaratnam, 2013. "Condition-number-regularized covariance estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 75(3), pages 427-450, June.
    19. Pei Wang & Dennis L. Chao & Li Hsu, 2011. "Learning Oncogenic Pathways from Binary Genomic Instability Data," Biometrics, The International Biometric Society, vol. 67(1), pages 164-173, March.
    20. Matteo Barigozzi & Marc Hallin, 2015. "Networks, Dynamic Factors, and the Volatility Analysis of High-Dimensional Financial Series," Working Papers ECARES ECARES 2015-34, ULB -- Universite Libre de Bruxelles.
    21. Rajaratnam, Bala & Salzman, Julia, 2013. "Best permutation analysis," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 193-223.
    22. repec:bla:jorssc:v:66:y:2017:i:3:p:581-605 is not listed on IDEAS
    23. Anufriev, Mikhail & Panchenko, Valentyn, 2015. "Connecting the dots: Econometric methods for uncovering networks with an application to the Australian financial institutions," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 241-255.
    24. repec:eee:jmvana:v:161:y:2017:i:c:p:172-190 is not listed on IDEAS

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