Abstract
AbstractWe review the graphics for studying the net‐effects of predictors, including both the global and local net‐effect plots. Then some new definitions of net‐effects and corresponding graphical methods are introduced for studying and visualizing the main and interaction net‐effects of the mean functions and the distribution functions. A sufficient dimension reduction method, called central solution subspace bivariate sliced inverse regression (CSS‐BiSIR), is proposed for reducing the size of the graphical problem. This facilitates the graphical interpretations of the net‐effects, and also allows us to visualize the net‐effects of nonelliptically distributed predictors. WIREs Comput Stat 2013, 5:105–113. doi: 10.1002/wics.1247This article is categorized under: Statistical and Graphical Methods of Data Analysis > Dimension Reduction Statistical and Graphical Methods of Data Analysis > Statistical Graphics and Visualization
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