Dimension-Reduction in Binary Response Regression
نویسندگان
چکیده
The idea of dimension-reduction without loss of information can be quite helpful for guiding the construction of summary plots in regression without requiring a pre-specified model. Focusing on the central subspace, we investigate such “sufficient” dimension-reduction in regressions with a binary response. Three existing methods, SIR and pHd and SAVE, and one new method DOC are studied for their ability to estimate the central subspace and produce sufficient summary plots. Combining these numerical methods with the graphical methods proposed by Cook (1996) leads to a novel paradigm for the analysis of binary response regressions.
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