Pooled marginal slicing approach via SIR α with discrete covariables

Benoît Liquet, Jérôme Saracco*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


In this paper, we consider a semiparametric regression model involving both p-dimensional quantitative covariable X and categorical predictor Z, and including a dimension reduction of X via K indices Xβ k . The dependent variable Y can be real or q-dimensional. We propose an approach based on SIR α and pooled marginal slicing methods in order to estimate the space spanned by the β k 's. We establish n} -consistency of the proposed estimator. Simulation studies show the numerical qualities of our estimator.

Original languageEnglish
Pages (from-to)599-617
Number of pages19
JournalComputational Statistics
Issue number4
Publication statusPublished - Dec 2007
Externally publishedYes


  • Discrete predictor
  • Semiparametric regression model
  • Sliced inverse regression (SIR)
  • Pooled marginal slicing (PMS)


Dive into the research topics of 'Pooled marginal slicing approach via SIR <sub>α</sub> with discrete covariables'. Together they form a unique fingerprint.

Cite this