Sufficient dimension reduction and graphics in regression

Francesca Chiaromonte, R. Dennis Cook

Research output: Contribution to journalReview articlepeer-review

27 Scopus citations


In this article, we review, consolidate and extend a theory for sufficient dimension reduction in regression settings. This theory provides a powerful context for the construction, characterization and interpretation of low-dimensional displays of the data, and allows us to turn graphics into a consistent and theoretically motivated methodological body. In this spirit, we propose an iterative graphical procedure for estimating the meta-parameter which lies at the core of sufficient dimension reduction; namely, the central dimension-reduction subspace.

Original languageEnglish (US)
Pages (from-to)768-795
Number of pages28
JournalAnnals of the Institute of Statistical Mathematics
Issue number4
StatePublished - Dec 1 2002

All Science Journal Classification (ASJC) codes

  • Statistics and Probability


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