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Technometrics Volume 57, 2015 - Issue 1
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Original Articles

Simultaneous Envelopes for Multivariate Linear Regression

R. Dennis CookSchool of Statistics, University of Minnesota, Minneapolis, MN55455 ([email protected])
&
Xin ZhangDepartment of Statistics Florida State University, Tallahassee, FL32306 ([email protected])
Pages 11-25 | Received 01 Mar 2013, Published online: 04 Mar 2015

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Read on this site (7)

Zhihua Su, Bing Li & Dennis Cook. (2023) Envelope Model for Function-on-Function Linear Regression. Journal of Computational and Graphical Statistics 32:4, pages 1624-1635.
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Jing Zhang & Zhensheng Huang. (2022) Efficient simultaneous partial envelope model in multivariate linear regression. Journal of Statistical Computation and Simulation 92:7, pages 1373-1400.
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Xin Zhang & Qing Mai. (2019) Efficient Integration of Sufficient Dimension Reduction and Prediction in Discriminant Analysis. Technometrics 61:2, pages 259-272.
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Xin Zhang & Lexin Li. (2017) Tensor Envelope Partial Least-Squares Regression. Technometrics 59:4, pages 426-436.
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Lexin Li & Xin Zhang. (2017) Parsimonious Tensor Response Regression. Journal of the American Statistical Association 112:519, pages 1131-1146.
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R. Dennis Cook & Xin Zhang. (2016) Algorithms for Envelope Estimation. Journal of Computational and Graphical Statistics 25:1, pages 284-300.
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R. Dennis Cook & Xin Zhang. (2015) Foundations for Envelope Models and Methods. Journal of the American Statistical Association 110:510, pages 599-611.
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Articles from other publishers (29)

R. Dennis Cook, Liliana Forzani & Lan Liu. (2023) Envelopes for multivariate linear regression with linearly constrained coefficients. Scandinavian Journal of Statistics.
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R. Dennis Cook & Liliana Forzani. (2023) On the role of partial least squares in path analysis for the social sciences. Journal of Business Research 167, pages 114132.
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R. Dennis Cook, Liliana Forzani & Lan Liu. (2023) Partial least squares for simultaneous reduction of response and predictor vectors in regression. Journal of Multivariate Analysis 196, pages 105163.
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Yanbo Shen, Yeonhee Park, Saptarshi Chakraborty & Chunming Zhang. (2023) Bayesian Simultaneous Partial Envelope Model with Application to an Imaging Genetics Analysis. The New England Journal of Statistics in Data Science, pages 1-33.
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Qing Mai & Xin Zhang. 2023. Springer Handbook of Engineering Statistics. Springer Handbook of Engineering Statistics 817 829 .
Said el Bouhaddani, Hae-Won Uh, Geurt Jongbloed & Jeanine Houwing-Duistermaat. (2022) Statistical Integration of Heterogeneous Omics Data: Probabilistic Two-Way Partial Least Squares (PO2PLS). Journal of the Royal Statistical Society Series C: Applied Statistics 71:5, pages 1451-1470.
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Paul May, Matthew Biesecker & Hossein Moradi Rekabdarkolaee. (2022) Response envelopes for linear coregionalization models. Journal of Multivariate Analysis 192, pages 105015.
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R. Dennis Cook. (2022) A slice of multivariate dimension reduction. Journal of Multivariate Analysis 188, pages 104812.
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Hossein Baghishani & Jamil Ownuk. 2022. Innovations in Multivariate Statistical Modeling. Innovations in Multivariate Statistical Modeling 169 185 .
Linquan Ma, Lan Liu & Wei Yang. (2021) Envelope method with ignorable missing data. Electronic Journal of Statistics 15:2.
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Minji Lee & Zhihua Su. (2020) A Review of Envelope Models. International Statistical Review 88:3, pages 658-676.
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X Zhang, C E Lee & X Shao. (2020) Envelopes in multivariate regression models with nonlinearity and heteroscedasticity. Biometrika 107:4, pages 965-981.
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Raju Rimal, Trygve Almøy & Solve Sæbø. (2020) Comparison of multi-response estimation methods. Chemometrics and Intelligent Laboratory Systems 205, pages 104093.
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R. Dennis Cook & Liliana Forzani. (2020) Envelopes: A new chapter in partial least squares regression. Journal of Chemometrics 34:10.
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Jia Zhang & Xin Chen. (2020) Principal envelope model. Journal of Statistical Planning and Inference 206, pages 249-262.
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R. Dennis Cook. (2019) Envelope methods. WIREs Computational Statistics 12:2.
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Yuyang Shi, Linquan Ma & Lan Liu. (2020) Mixed effects envelope models. Stat 9:1.
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Guang-Hui Fu, Min-Jie Zong, Feng-Hua Wang & Lun-Zhao Yi. (2019) A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data. International Journal of Analytical Chemistry 2019, pages 1-12.
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Raju Rimal, Trygve Almøy & Solve Sæbø. (2019) Comparison of multi-response prediction methods. Chemometrics and Intelligent Laboratory Systems 190, pages 10-21.
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R. Dennis Cook. 2018. An Introduction to Envelopes. An Introduction to Envelopes 273 282 .
Said el Bouhaddani, Hae-Won Uh, Caroline Hayward, Geurt Jongbloed & Jeanine Houwing-Duistermaat. (2018) Probabilistic partial least squares model: Identifiability, estimation and application. Journal of Multivariate Analysis 167, pages 331-346.
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Inge Svein Helland, Solve Saebø, Trygve Almøy & Raju Rimal. (2018) Model and estimators for partial least squares regression. Journal of Chemometrics 32:9, pages e3044.
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Raju Rimal, Trygve Almøy & Solve Sæbø. (2018) A tool for simulating multi-response linear model data. Chemometrics and Intelligent Laboratory Systems 176, pages 1-10.
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R. Dennis Cook. (2018) Principal Components, Sufficient Dimension Reduction, and Envelopes. Annual Review of Statistics and Its Application 5:1, pages 533-559.
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Shanshan Ding & R. Dennis Cook. (2018) Matrix Variate Regressions and Envelope Models. Journal of the Royal Statistical Society Series B: Statistical Methodology 80:2, pages 387-408.
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Xin Zhang & Qing Mai. (2018) Model-free envelope dimension selection. Electronic Journal of Statistics 12:2.
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Xin Zhang, Chong Wang & Yichao Wu. (2018) Functional envelope for model-free sufficient dimension reduction. Journal of Multivariate Analysis 163, pages 37-50.
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R. Dennis Cook, Liliana Forzani & Zhihua Su. (2016) A note on fast envelope estimation. Journal of Multivariate Analysis 150, pages 42-54.
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Gen Li, Dan Yang, Andrew B. Nobel & Haipeng Shen. (2016) Supervised singular value decomposition and its asymptotic properties. Journal of Multivariate Analysis 146, pages 7-17.
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