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Integrated Partial Sufficient Dimension Reduction with Heavily Unbalanced Categorical Predictors
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 Title & Authors
Integrated Partial Sufficient Dimension Reduction with Heavily Unbalanced Categorical Predictors
Yoo, Jae-Keun;
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 Abstract
In this paper, we propose an approach to conduct partial sufficient dimension reduction with heavily unbalanced categorical predictors. For this, we consider integrated categorical predictors and investigate certain conditions that the integrated categorical predictor is fully informative to partial sufficient dimension reduction. For illustration, the proposed approach is implemented on optimal partial sliced inverse regression in simulation and data analysis.
 Keywords
Integration;partial dimension subspaces;sufficient dimension reduction;regression;unbalanced categorical predictors;
 Language
English
 Cited by
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Communications for Statistical Applications and Methods, 2015. vol.22. 3, pp.305-312 crossref(new window)
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A link-free approach for testing common indices for three or more multi-index models, Journal of Multivariate Analysis, 2017, 153, 236  crossref(new windwow)
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Generalized Partially Double-Index Model: Bootstrapping and Distinguishing Values, Communications for Statistical Applications and Methods, 2015, 22, 3, 305  crossref(new windwow)
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