On Partial Sufficient Dimension Reduction With Applications to Partially Linear Multi-Index Models
部分充分降维及其在部分线性多指标模型中的应用
Partial dimension reduction is a general method to seek informative convex combinations of predictors of primary interest, which includes dimension reduction as its special case when the predictors in the remaining part are constants. In this article, we propose a novel method to conduct partial dimension reduction estimation for predictors of primary interest without assuming that the remaining predictors are categorical. To this end, we first take the dichotomization step…