Pooled marginal slicing approach via SIR\({}_\alpha\) with discrete covariates
type: Item
instance of: scholarly article
title: Pooled marginal slicing approach via SIR\({}_\alpha\) with discrete covariates
zbMATH Open document ID: 1194.62049
author: Benoit Liquet
author: Jérôme Saracco
published in: Computational Statistics
publication date: 2010-04-22T00:00:00Z
review text: A sliced inverse regression (SIR) technique is considered in the case of multivariate responses and the presence of some categorical predictor which stratifies the analyzed population. Two pooled marginal slicing estimators are proposed for the effective dimension reduction space, utilizing mixed SIR-I and SIR-II approaches. They can be used for homoscedastic and heteroscedastic errors. Asymptotic normality of the estimates is established. Results of simulations are presented.
Mathematics Subject Classification ID: 62G08
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62G20
zbMATH DE Number: 5697312
zbMATH Keywords: effective dimension reduction space
zbMATH Keywords: pooled marginal slicing estimate
zbMATH Keywords: asymptotic normality
MaRDI profile type: Publication
full work available at URL: s00180-007-0078-4
OpenAlex ID: W2045917387
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DOI: 10.1007/S00180-007-0078-4
description: scientific article; zbMATH DE number 5697312