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• W3103296927 abstract "We study the asymptotic behavior of a class of methods for sufficient dimension reduction in high-dimension regressions, as the sample size and number of predictors grow in various alignments. It is demonstrated that these methods are consistent in a variety of settings, particularly in abundant regressions where most predictors contribute some information on the response, and oracle rates are possible. Simulation results are presented to support the theoretical conclusion." @default.
• W3103296927 created "2020-11-23" @default.
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• W3103296927 date "2012-02-01" @default.
• W3103296927 modified "2023-10-17" @default.
• W3103296927 title "Estimating sufficient reductions of the predictors in abundant high-dimensional regressions" @default.
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• W3103296927 doi "https://doi.org/10.1214/11-aos962" @default.
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