Sliced inverse regression for multivariate response regression |
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Authors: | Heng-Hui Lue |
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Institution: | Department of Statistics, Tunghai University, Taiwan |
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Abstract: | We consider a regression analysis of multivariate response on a vector of predictors. In this article, we develop a sliced inverse regression-based method for reducing the dimension of predictors without requiring a prespecified parametric model. Our proposed method preserves as much regression information as possible. We derive the asymptotic weighted chi-squared test for dimension. Simulation results are reported and comparisons are made with three methods—most predictable variates, k-means inverse regression and canonical correlation approach. |
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Keywords: | Canonical correlation Dimension reduction Most predictable variates Multivariate response Sliced inverse regression |
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