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On the extension of sliced average variance estimation to multivariate regression

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Abstract

Many sufficient dimension reduction methods for univariate regression have been extended to multivariate regression. Sliced average variance estimation (SAVE) has the potential to recover more reductive information and recent development enables us to test the dimension and predictor effects with distributions commonly used in the literature. In this paper, we aim to extend the functionality of the SAVE to multivariate regression. Toward the goal, we propose three new methods. Numerical studies and real data analysis demonstrate that the proposed methods perform well.

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Correspondence to Jae Keun Yoo.

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The views expressed in this paper are the author own but do not necessarily represent the views of Fannie Mae.

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Yoo, J.K., Lee, K. & Wu, S. On the extension of sliced average variance estimation to multivariate regression. Stat Methods Appl 19, 529–540 (2010). https://doi.org/10.1007/s10260-010-0145-9

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