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Input selection and shrinkage in multiresponse linear regression

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  • Simila, Timo
  • Tikka, Jarkko

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  • Simila, Timo & Tikka, Jarkko, 2007. "Input selection and shrinkage in multiresponse linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 406-422, September.
    • Handle: RePEc:eee:csdana:v:52:y:2007:i:1:p:406-422
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    References listed on IDEAS

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    1. P. J. Brown & M. Vannucci & T. Fearn, 2002. "Bayes model averaging with selection of regressors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 519-536, August.
    2. Abraham, Bovas & Merola, Giovanni, 2005. "Dimensionality reduction approach to multivariate prediction," Computational Statistics & Data Analysis, Elsevier, vol. 48(1), pages 5-16, January.
    3. Ming Yuan & Yi Lin, 2006. "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 49-67, February.
    4. Leo Breiman & Jerome H. Friedman, 1997. "Predicting Multivariate Responses in Multiple Linear Regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(1), pages 3-54.
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    Cited by:

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    2. Luo, Ruiyan & Qi, Xin, 2017. "Signal extraction approach for sparse multivariate response regression," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 83-97.
    3. 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.
    4. Bingzhen Chen & Wenjuan Zhai & Lingchen Kong, 2022. "Variable selection and collinearity processing for multivariate data via row-elastic-net regularization," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 79-96, March.
    5. Shan Luo, 2020. "Variable selection in high-dimensional sparse multiresponse linear regression models," Statistical Papers, Springer, vol. 61(3), pages 1245-1267, June.
    6. Marra, Giampiero & Wood, Simon N., 2011. "Practical variable selection for generalized additive models," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2372-2387, July.
    7. Jesús Alejandro Navarro Acosta & Valeria Soto Mendoza & Laura Policardo & Edgar Javier Sánchez Carrera, 2025. "Modeling economic growth in pandemic times with machine learning regression algorithms," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 20(1), pages 1-33, Enero - M.
    8. Jeongsub Choi & Mengmeng Zhu & Jihoon Kang & Myong K. Jeong, 2024. "Convolutional neural network based multi-input multi-output model for multi-sensor multivariate virtual metrology in semiconductor manufacturing," Annals of Operations Research, Springer, vol. 339(1), pages 185-201, August.
    9. Xingpei Yan & Zheng Zhu, 2020. "City-Level China Traffic Safety Analysis via Multi-Output and Clustering-Based Regression Models," Sustainability, MDPI, vol. 12(8), pages 1-13, April.

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