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Nonparametric estimation of large covariance matrices of longitudinal data

Citations

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Cited by:

  1. Xueying Zheng & Wing Fung & Zhongyi Zhu, 2013. "Robust estimation in joint mean–covariance regression model for longitudinal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(4), pages 617-638, August.
  2. Yumou Qiu & Song Xi Chen, 2015. "Bandwidth Selection for High-Dimensional Covariance Matrix Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1160-1174, September.
  3. Daye, Z. John & Jeng, X. Jessie, 2009. "Shrinkage and model selection with correlated variables via weighted fusion," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1284-1298, February.
  4. Wang, Xuanci & Zhang, Bin, 2024. "Target selection in shrinkage estimation of covariance matrix: A structural similarity approach," Statistics & Probability Letters, Elsevier, vol. 208(C).
  5. Jia, Shengji & Zhang, Chunming & Lu, Haoran, 2022. "Covariance function versus covariance matrix estimation in efficient semi-parametric regression for longitudinal data analysis," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
  6. Cederbaum, Jona & Scheipl, Fabian & Greven, Sonja, 2018. "Fast symmetric additive covariance smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 25-41.
  7. Lam, Clifford, 2008. "Estimation of large precision matrices through block penalization," LSE Research Online Documents on Economics 31543, London School of Economics and Political Science, LSE Library.
  8. Dursun Aydin & Ersin Yilmaz, 2021. "Censored Nonparametric Time-Series Analysis with Autoregressive Error Models," Computational Economics, Springer;Society for Computational Economics, vol. 58(2), pages 169-202, August.
  9. Kiranmoy Das & Michael J. Daniels, 2014. "A semiparametric approach to simultaneous covariance estimation for bivariate sparse longitudinal data," Biometrics, The International Biometric Society, vol. 70(1), pages 33-43, March.
  10. H. J. Turtle & Kainan Wang, 2014. "Modeling Conditional Covariances With Economic Information Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(2), pages 217-236, April.
  11. Jianqing Fan & Yuan Liao & Han Liu, 2016. "An overview of the estimation of large covariance and precision matrices," Econometrics Journal, Royal Economic Society, vol. 19(1), pages 1-32, February.
  12. Chen, Song Xi & Li, Jun & Zhong, Pingshou, 2014. "Two-Sample Tests for High Dimensional Means with Thresholding and Data Transformation," MPRA Paper 59815, University Library of Munich, Germany.
  13. Xiaoping Zhou & Dmitry Malioutov & Frank J. Fabozzi & Svetlozar T. Rachev, 2014. "Smooth monotone covariance for elliptical distributions and applications in finance," Quantitative Finance, Taylor & Francis Journals, vol. 14(9), pages 1555-1571, September.
  14. Chen, Jia & Li, Degui & Linton, Oliver, 2019. "A new semiparametric estimation approach for large dynamic covariance matrices with multiple conditioning variables," Journal of Econometrics, Elsevier, vol. 212(1), pages 155-176.
  15. Manuel Febrero-Bande, 2016. "Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 35-40, March.
  16. Benjamin Poignard & Manabu Asai, 2023. "Estimation of high-dimensional vector autoregression via sparse precision matrix," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 307-326.
  17. Christopher Withers & Saralees Nadarajah, 2014. "Non-parametric confidence intervals for covariance and correlation," METRON, Springer;Sapienza Università di Roma, vol. 72(3), pages 283-306, October.
  18. Abadir, Karim M. & Distaso, Walter & Žikeš, Filip, 2014. "Design-free estimation of variance matrices," Journal of Econometrics, Elsevier, vol. 181(2), pages 165-180.
  19. Shin, Hyejin, 2008. "An extension of Fisher's discriminant analysis for stochastic processes," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1191-1216, July.
  20. Beate Franke & Jean-FRANçois Plante & Ribana Roscher & En-shiun Annie Lee & Cathal Smyth & Armin Hatefi & Fuqi Chen & Einat Gil & Alexander Schwing & Alessandro Selvitella & Michael M. Hoffman & Roger, 2016. "Statistical Inference, Learning and Models in Big Data," International Statistical Review, International Statistical Institute, vol. 84(3), pages 371-389, December.
  21. Jianqing Fan & Lingzhou Xue & Hui Zou, 2016. "Multitask Quantile Regression Under the Transnormal Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1726-1735, October.
  22. Muschinski, Thomas & Mayr, Georg J. & Simon, Thorsten & Umlauf, Nikolaus & Zeileis, Achim, 2024. "Cholesky-based multivariate Gaussian regression," Econometrics and Statistics, Elsevier, vol. 29(C), pages 261-281.
  23. Xi Luo, 2011. "Recovering Model Structures from Large Low Rank and Sparse Covariance Matrix Estimation," Papers 1111.1133, arXiv.org, revised Mar 2013.
  24. Sung, Bongjung & Lee, Jaeyong, 2023. "Covariance structure estimation with Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  25. Yan Zhou & Peter X.‐K. Song & Xiaoquan Wen, 2021. "Structural factor equation models for causal network construction via directed acyclic mixed graphs," Biometrics, The International Biometric Society, vol. 77(2), pages 573-586, June.
  26. Chen, Ziqi & Shi, Ning-Zhong & Gao, Wei & Tang, Man-Lai, 2011. "Efficient semiparametric estimation via Cholesky decomposition for longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3344-3354, December.
  27. Manuel Febrero-Bande, 2016. "Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 35-40, March.
  28. Chen, Songxi, 2012. "Two Sample Tests for High Dimensional Covariance Matrices," MPRA Paper 46026, University Library of Munich, Germany.
  29. Zhang, Qiang & Ip, Edward H. & Pan, Junhao & Plemmons, Robert, 2017. "Individual-specific, sparse inverse covariance estimation in generalized estimating equations," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 96-103.
  30. Feng, Yuanhua & Yu, Keming, 2006. "Nonparametric estimation of time-varying covariance matrix in a slowly changing vector random walk model," MPRA Paper 1597, University Library of Munich, Germany.
  31. Gautam Sabnis & Debdeep Pati & Anirban Bhattacharya, 2019. "Compressed Covariance Estimation with Automated Dimension Learning," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 466-481, December.
  32. Peter Bickel & Bo Li & Alexandre Tsybakov & Sara Geer & Bin Yu & Teófilo Valdés & Carlos Rivero & Jianqing Fan & Aad Vaart, 2006. "Regularization in statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 15(2), pages 271-344, September.
  33. Shaojun Guo & John Leigh Box & Wenyang Zhang, 2017. "A Dynamic Structure for High-Dimensional Covariance Matrices and Its Application in Portfolio Allocation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(517), pages 235-253, January.
  34. Huaihou Chen & Yuanjia Wang, 2011. "A Penalized Spline Approach to Functional Mixed Effects Model Analysis," Biometrics, The International Biometric Society, vol. 67(3), pages 861-870, September.
  35. Lam, Clifford & Fan, Jianqing, 2009. "Sparsistency and rates of convergence in large covariance matrix estimation," LSE Research Online Documents on Economics 31540, London School of Economics and Political Science, LSE Library.
  36. Mao, Jie & Zhu, Zhongyi & Fung, Wing K., 2011. "Joint estimation of mean-covariance model for longitudinal data with basis function approximations," Computational Statistics & Data Analysis, Elsevier, vol. 55(2), pages 983-992, February.
  37. 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.
  38. He, Jing & Chen, Song Xi, 2016. "Testing super-diagonal structure in high dimensional covariance matrices," Journal of Econometrics, Elsevier, vol. 194(2), pages 283-297.
  39. Song Song, 2011. "Dynamic Large Spatial Covariance Matrix Estimation in Application to Semiparametric Model Construction via Variable Clustering: the SCE approach," Papers 1106.3921, arXiv.org, revised Jun 2011.
  40. Lopes, Hedibert F. & McCulloch, Robert E. & Tsay, Ruey S., 2022. "Parsimony inducing priors for large scale state–space models," Journal of Econometrics, Elsevier, vol. 230(1), pages 39-61.
  41. Zvi Bodie & Jérôme Detemple & Marcel Rindisbacher, 2009. "Life-Cycle Finance and the Design of Pension Plans," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 249-286, November.
  42. Rui Li & Chenlei Leng & Jinhong You, 2017. "A Semiparametric Regression Model for Longitudinal Data with Non-stationary Errors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 932-950, December.
  43. John Stephen Yap & Jianqing Fan & Rongling Wu, 2009. "Nonparametric Modeling of Longitudinal Covariance Structure in Functional Mapping of Quantitative Trait Loci," Biometrics, The International Biometric Society, vol. 65(4), pages 1068-1077, December.
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