Estimating Sufficient Reductions of the Predictors in Abundant High-dimensional Regressions by R. Dennis Cook1, Liliana Forzani


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… (More)


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