Abstract
Regression analysis is the study of how a response variable depends on one or more predictors. In regression graphics we pursue low-dimensional sufficient summary plots. These plots, which do not require a model for their construction, contain all the information on the response that is available from the predictors. They can be used to visualize dependence, to discover unexpected relationships, to guide the choice of a first model, and to check plausible models. This article covers the foundations for sufficient summary plots and how they can be estimated and used in practice. Their relationship to standard model-based graphics such as residual plots is covered as well.
Original language | English (US) |
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Title of host publication | International Encyclopedia of the Social & Behavioral Sciences: Second Edition |
Publisher | Elsevier Inc. |
Pages | 157-161 |
Number of pages | 5 |
ISBN (Electronic) | 9780080970875 |
ISBN (Print) | 9780080970868 |
DOIs | |
State | Published - Mar 26 2015 |
Bibliographical note
Publisher Copyright:© 2015 Elsevier Ltd. All rights reserved.
Keywords
- Mean function
- Model-based graphics
- Regression analysis
- Response
- Summary plots
- Variance function