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Dimension reduction and coefficient estimation in multivariate linear regression

Citations

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Cited by:

  1. Marie Levakova & Susanne Ditlevsen, 2024. "Penalisation Methods in Fitting High‐Dimensional Cointegrated Vector Autoregressive Models: A Review," International Statistical Review, International Statistical Institute, vol. 92(2), pages 160-193, August.
  2. Pan Shang & Lingchen Kong, 2021. "Regularization Parameter Selection for the Low Rank Matrix Recovery," Journal of Optimization Theory and Applications, Springer, vol. 189(3), pages 772-792, June.
  3. Zehua Chen & Yiwei Jiang, 2020. "A two-stage sequential conditional selection approach to sparse high-dimensional multivariate regression models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 65-90, February.
  4. Luwan Zhang & Grace Wahba & Ming Yuan, 2016. "Distance shrinkage and Euclidean embedding via regularized kernel estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 849-867, September.
  5. Qiu, Yue & Zheng, Yuchen, 2023. "Improving box office projections through sentiment analysis: Insights from regularization-based forecast combinations," Economic Modelling, Elsevier, vol. 125(C).
  6. Kargin, Vladislav, 2015. "On estimation in the reduced-rank regression with a large number of responses and predictors," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 377-394.
  7. Chao, Shih-Kang & Härdle, Wolfgang K. & Huang, Chen, 2018. "Multivariate factorizable expectile regression with application to fMRI data," Computational Statistics & Data Analysis, Elsevier, vol. 121(C), pages 1-19.
  8. Härdle, Wolfgang Karl & Huang, Chen & Chao, Shih-Kang, 2016. "Factorisable sparse tail event curves with expectiles," SFB 649 Discussion Papers 2016-018, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  9. Fujikoshi, Yasunori & Sakurai, Tetsuro, 2016. "High-dimensional consistency of rank estimation criteria in multivariate linear model," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 199-212.
  10. Tsukuda, Koji & Matsuura, Shun, 2025. "Estimators for multivariate allometric regression model," Journal of Multivariate Analysis, Elsevier, vol. 210(C).
  11. Bamdev Mishra & Gilles Meyer & Silvère Bonnabel & Rodolphe Sepulchre, 2014. "Fixed-rank matrix factorizations and Riemannian low-rank optimization," Computational Statistics, Springer, vol. 29(3), pages 591-621, June.
  12. repec:hum:wpaper:sfb649dp2016-058 is not listed on IDEAS
  13. repec:hum:wpaper:sfb649dp2016-018 is not listed on IDEAS
  14. Chao, Shih-Kang & Härdle, Wolfgang Karl & Yuan, Ming, 2015. "Factorisable sparse tail event curves," SFB 649 Discussion Papers 2015-034, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  15. Luo, Chongliang & Liang, Jian & Li, Gen & Wang, Fei & Zhang, Changshui & Dey, Dipak K. & Chen, Kun, 2018. "Leveraging mixed and incomplete outcomes via reduced-rank modeling," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 378-394.
  16. An, Baiguo & Zhang, Beibei, 2017. "Simultaneous selection of predictors and responses for high dimensional multivariate linear regression," Statistics & Probability Letters, Elsevier, vol. 127(C), pages 173-177.
  17. repec:hum:wpaper:sfb649dp2015-034 is not listed on IDEAS
  18. Ke, Yuan & Zhang, Rongmao & Zhang, Wenyang & Zou, Changliang, 2026. "Hypothesis test in high dimensional multi-response linear models," Computational Statistics & Data Analysis, Elsevier, vol. 215(C).
  19. Chao, Shih-Kang & Härdle, Wolfgang Karl & Huang, Chen, 2016. "Multivariate factorisable sparse asymmetric least squares regression," SFB 649 Discussion Papers 2016-058, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  20. Miyashiro, Ryuhei & Takano, Yuichi, 2015. "Mixed integer second-order cone programming formulations for variable selection in linear regression," European Journal of Operational Research, Elsevier, vol. 247(3), pages 721-731.
  21. Kohei Yoshikawa & Shuichi Kawano, 2023. "Sparse reduced-rank regression for simultaneous rank and variable selection via manifold optimization," Computational Statistics, Springer, vol. 38(1), pages 53-75, March.
  22. Vladimir M. Cvetković & Neda Nikolić & Adem Ocal & Jovana Martinović & Aleksandar Dragašević, 2022. "A Predictive Model of Pandemic Disaster Fear Caused by Coronavirus (COVID-19): Implications for Decision-Makers," IJERPH, MDPI, vol. 19(2), pages 1-27, January.
  23. Mishra, Aditya & Dey, Dipak K. & Chen, Yong & Chen, Kun, 2021. "Generalized co-sparse factor regression," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  24. Jin Liu & Jian Huang & Shuangge Ma, 2012. "Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-12, December.
  25. Changliang Zou & Xianghui Ning & Fugee Tsung, 2012. "LASSO-based multivariate linear profile monitoring," Annals of Operations Research, Springer, vol. 192(1), pages 3-19, January.
  26. Li, Mei & Kong, Lingchen, 2019. "Double fused Lasso penalized LAD for matrix regression," Applied Mathematics and Computation, Elsevier, vol. 357(C), pages 119-138.
  27. Kharratzadeh, Milad & Coates, Mark, 2017. "Semi-parametric order-based generalized multivariate regression," Journal of Multivariate Analysis, Elsevier, vol. 156(C), pages 89-102.
  28. Donghwi Nam & Ja-Yong Koo & Kwan-Young Bak, 2025. "Dimensionality reduction in multivariate nonparametric regression via nuclear norm penalization," Statistical Papers, Springer, vol. 66(3), pages 1-33, April.
  29. Yiting Ma & Pan Shang & Lingchen Kong, 2025. "Tuning parameter selection for the adaptive nuclear norm regularized trace regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 77(3), pages 491-516, June.
  30. Kun Chen & Yanyuan Ma, 2017. "Analysis of Double Single Index Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(1), pages 1-20, March.
  31. Goh, Gyuhyeong & Dey, Dipak K. & Chen, Kun, 2017. "Bayesian sparse reduced rank multivariate regression," Journal of Multivariate Analysis, Elsevier, vol. 157(C), pages 14-28.
  32. Matsui, Hidetoshi, 2014. "Variable and boundary selection for functional data via multiclass logistic regression modeling," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 176-185.
  33. 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.
  34. Yoshio Takane & Sunho Jung, 2008. "Regularized Partial and/or Constrained Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 73(4), pages 671-690, December.
  35. Chen, Canyi & Xu, Wangli & Zhu, Liping, 2022. "Distributed estimation in heterogeneous reduced rank regression: With application to order determination in sufficient dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 190(C).
  36. Fanhua Shang & Yuanyuan Liu & Fanjie Shang & Hongying Liu & Lin Kong & Licheng Jiao, 2020. "A Unified Scalable Equivalent Formulation for Schatten Quasi-Norms," Mathematics, MDPI, vol. 8(8), pages 1-19, August.
  37. Arash Karimzadeh & Omidreza Shoghli & Sepehr Sabeti & Hamed Tabkhi, 2022. "Multi-Asset Defect Hotspot Prediction for Highway Maintenance Management: A Risk-Based Machine Learning Approach," Sustainability, MDPI, vol. 14(9), pages 1-27, April.
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