A selective review of sufficient dimension reduction for multivariate response regression
It provides a selective review for researchers in statistics, but it is incremental as it summarizes existing methods without novel contributions.
The paper reviews sufficient dimension reduction (SDR) estimators for multivariate response regression, categorizing them into inverse regression and forward regression families without presenting new results or numbers.
We review sufficient dimension reduction (SDR) estimators with multivariate response in this paper. A wide range of SDR methods are characterized as inverse regression SDR estimators or forward regression SDR estimators. The inverse regression family include pooled marginal estimators, projective resampling estimators, and distance-based estimators. Ordinary least squares, partial least squares, and semiparametric SDR estimators, on the other hand, are discussed as estimators from the forward regression family.