Manual controls for high-dimensional data projections

Dianne Cook, Andreas Buja

Research output: Contribution to journalArticleResearchpeer-review

25 Citations (Scopus)


Projections of high-dimensional data onto low-dimensional subspaces provide insightful views for understanding multivariate relationships. This article discusses how to manually control the variable contributions to the projection. The user has control of the way a particular variable contributes to the viewed projection and can interactively adjust the variable's contribution. These manual controls complement the automatic views provided by a grand tour, or a guided tour, and give greatly improved flexibility to data analysts.

Original languageEnglish
Pages (from-to)464-480
Number of pages17
JournalJournal of Computational and Graphical Statistics
Issue number4
Publication statusPublished - 1 Jan 1997
Externally publishedYes


  • Data visualization
  • Dynamic graphics
  • Grand tour
  • Multivariate analysis
  • Projection pursuit

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