A minimum discrepancy approach to multivariate dimension reduction via \(k\)-means inverse regression

DOI10.4310/SII.2009.V2.N4.A11zbMath1245.62079MaRDI QIDQ440158

Xuerong Meggie Wen, Akim Adekpedjou, C. Messan Setodji

Publication date: 18 August 2012

Published in: Statistics and Its Interface (Search for Journal in Brave)

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nonparametric inference (62G99)

Related Items (3)

A selective review of sufficient dimension reduction for multivariate response regression ⋮ Data-driven slicing for dimension reduction in regressions: A likelihood-ratio approach ⋮ Advanced topics in sliced inverse regression

This page was built for publication: A minimum discrepancy approach to multivariate dimension reduction via \(k\)-means inverse regression