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Regression Graphics. Ideas for Studying Regressions Through Graphics. Edition No. 1. Wiley Series in Probability and Statistics

  • ID: 2174509
  • Book
  • October 1998
  • 349 Pages
  • John Wiley and Sons Ltd
An exploration of regression graphics through computer graphics.

Recent developments in computer technology have stimulated new and exciting uses for graphics in statistical analyses. Regression Graphics, one of the first graduate-level textbooks on the subject, demonstrates how statisticians, both theoretical and applied, can use these exciting innovations. After developing a relatively new regression context that requires few scope-limiting conditions, Regression Graphics guides readers through the process of analyzing regressions graphically and assessing and selecting models. This innovative reference makes use of a wide range of graphical tools, including 2D and 3D scatterplots, 3D binary response plots, and scatterplot matrices. Supplemented by a companion ftp site, it features numerous data sets and applied examples that are used to elucidate the theory.

Other important features of this book include:

Extensive coverage of a relatively new regression context based on dimension-reduction subspaces and sufficient summary plots

Graphical regression, an iterative visualization process for constructing sufficient regression views

Graphics for regressions with a binary response

Graphics for model assessment, including residual plots

Net-effects plots for assessing predictor contributions

Graphics for predictor and response transformations

Inverse regression methods

Access to a Web site of supplemental plots, data sets, and 3D color displays.

An ideal text for students in graduate-level courses on statistical analysis, Regression Graphics is also an excellent reference for professional statisticians.
Note: Product cover images may vary from those shown
Introduction to 2D Scatterplots.

Constructing 3D Scatterplots.

Interpreting 3D Scatterplots.

Binary Response Variables.

Dimension-Reduction Subspaces.

Graphical Regression.

Getting Numerical Help.

Graphical Regression Studies.

Inverse Regression Graphics.

Sliced Inverse Regression.

Principles Hessian Directions.

Studying Predictor Effects.

Predictor Transformations.

Graphics for Model Assessment.


Note: Product cover images may vary from those shown
R. Dennis Cook The University of Minnesota, St. Paul.
Note: Product cover images may vary from those shown