Linear Hypothesis: Regression (Graphics)

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish (US)
Title of host publicationInternational Encyclopedia of the Social & Behavioral Sciences: Second Edition
PublisherElsevier Inc.
Pages157-161
Number of pages5
ISBN (Electronic)9780080970875
ISBN (Print)9780080970868
DOIs
StatePublished - Mar 26 2015

Keywords

  • Mean function
  • Model-based graphics
  • Regression analysis
  • Response
  • Summary plots
  • Variance function

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  • Cite this

    Cook, R. D. (2015). Linear Hypothesis: Regression (Graphics). In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 157-161). Elsevier Inc.. https://doi.org/10.1016/B978-0-08-097086-8.42141-0