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Original Articles

Save: a method for dimension reduction and graphics in regression

Pages 2109-2121 | Received 01 May 1999, Published online: 27 Jun 2007

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Mètolidji Moquilas Raymond Affossogbe, Guy Martial Nkiet & Carlos Ogouyandjou. (2023) Smoothed average variance estimation for dimension reduction with functional data. Communications in Statistics - Theory and Methods 52:3, pages 806-829.
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Xin Chen, Jia Zhang & Wang Zhou. (2022) High-Dimensional Elliptical Sliced Inverse Regression in Non-Gaussian Distributions. Journal of Business & Economic Statistics 40:3, pages 1204-1215.
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Xin Cai, Guang Lin & Jinglai Li. (2021) Bayesian inverse regression for supervised dimension reduction with small datasets. Journal of Statistical Computation and Simulation 91:14, pages 2817-2832.
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Parimal Hor & Babulal Seal. (2019) SAVE: Robust or not?. Communications in Statistics - Simulation and Computation 48:10, pages 2855-2865.
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Qian Lin, Zhigen Zhao & Jun S. Liu. (2019) Sparse Sliced Inverse Regression via Lasso. Journal of the American Statistical Association 114:528, pages 1726-1739.
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M. Matilainen, C. Croux, K. Nordhausen & H. Oja. (2019) Sliced average variance estimation for multivariate time series. Statistics 53:3, pages 630-655.
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Junhua Zhang, Bingqing Lin, Yan Zhou & Jun Zhang. (2018) Dimension reduction regressions with measurement errors subject to additive distortion. Journal of Statistical Computation and Simulation 88:13, pages 2631-2649.
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Keunbaik Lee, Hyejin Song & Jae Keun Yoo. (2017) Dimension test approach of heteroscedasticity in the linear model. Communications in Statistics - Simulation and Computation 46:6, pages 4356-4366.
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Jae Keun Yoo. (2016) Sufficient dimension reduction through informative predictor subspace. Statistics 50:5, pages 1086-1099.
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Marie Chavent, Vanessa Kuentz, Benoıt Liquet & Jérôme Saracco. (2011) A Sliced Inverse Regression Approach for a Stratified Population. Communications in Statistics - Theory and Methods 40:21, pages 3857-3878.
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Vanessa Kuentz, Benoît Liquet & Jérôme Saracco. (2010) Bagging Versions of Sliced Inverse Regression. Communications in Statistics - Theory and Methods 39:11, pages 1985-1996.
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Li-Ping Zhu & Li-Xing Zhu. (2009) A data-adaptive hybrid method for dimension reduction. Journal of Nonparametric Statistics 21:7, pages 851-861.
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Heng-Hui Lue. (2008) Sliced Average Variance Estimation for Censored Data. Communications in Statistics - Theory and Methods 37:20, pages 3276-3286.
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D. J. Olive. 2004. Theory and Applications of Recent Robust Methods. Theory and Applications of Recent Robust Methods 221 233 .
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