Direction Estimation in Single-Index Regressions via Hilbert-Schmidt Independence Criterion

DOI10.5705/ss.2013.113OpenAlexW2156826956MaRDI QIDQ3449027

Nan Zhang, Xiangrong Yin

Publication date: 3 November 2015

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://semanticscholar.org/paper/bac464ebec7cf213fdd270ef3812314f66da9ddd

zbMATH Keywords

single-index modelssufficient dimension reductionpermutation testcentral subspaceHilbert-Schmidt independence criterion

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (7)

A brief review of linear sufficient dimension reduction through optimization ⋮ Direction Estimation in a General Regression Model with Discrete Predictors ⋮ Sufficient dimension reduction using Hilbert-Schmidt independence criterion ⋮ On bootstrap consistency of MAVE for single index models ⋮ Sufficient variable selection using independence measures for continuous response ⋮ Quasi-likelihood estimation of the single index conditional variance model ⋮ New estimation for heteroscedastic single-index measurement error models

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