An Introduction to Regression Graphics
Wiley (Publisher)
Published on 11. August 1994
Book
Hardback
280 pages
978-0-471-00839-2 (ISBN)
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Description
The current literature tends to focus on presentation graphics rather than regression graphics. This monograph covers the use of interactive computer graphics in regression analysis and emphasizes the analytical graphics that are used to discover the way information behaves. It introduces a number of new graphical methods that take advantage of high quality graphics, possible only with the computer hardware of today. The authors have written their own regression code software called R code. R code runs on Macintoshes, PCs with Windows, and UNIX workstations. The R code program is available on a disk accompanying this book.
More details
Series
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 244 mm
Width: 163 mm
Thickness: 26 mm
Weight
616 gr
ISBN-13
978-0-471-00839-2 (9780471008392)
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Schweitzer Classification
Persons
About the authors R. DENNIS COOK is Professor, Department of Applied Statistics, University of Minnesota. An active researcher in regression theory and methods, Dr. Cook is a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics, and is an elected member of the International Statistical Institute. Dr. Cook received his PhD degree in statistics from Kansas State University. SANFORD WEISBERG is Professor, Department of Applied Statistics, University of Minnesota. The author of Applied Linear Regression, Second Edition (Wiley), he is a Fellow of the American Statistical Association and an elected member of the International Statistical Institute. Dr. Weisberg received his PhD degree in statistics from Harvard University. The authors have jointly published about twenty works, including Residuals and Influence in Regression and a 1989 paper on regression graphics that earned the Jack Youden prize.
Content
Getting Started. Simple Regression Plots. Two--Dimensional Plots. Scatterplot Matrices. Three--Dimensional Plots. Visualizing Linear Regression with Two Predictors. Visualizing Regression Without Linearity. Finding Dimension. Predictor Transformations. Response Transformations. Checking Models. Assessing Predictors. Influence and Outliers. Confidence Regions. Appendices. References. Index.