Graphics for Regressions With a Binary Response
本文发展了中心降维子空间的概念，用于刻画二元响应变量与预测变量的依赖关系，并以此指导回归图形的构建与解读，提出了无需链接函数或残差的图形方法。
Abstract Central dimension-reduction subspaces, which characterize the dependence of a response variable on one or more predictors, are developed and then used to guide the construction and interpretation of graphics for regression problems with a binary response variable. Graphical methods requiring neither a link function nor residuals are suggested for both development and criticism of model components implied by the central dimension-reduction subspace.