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June 2004 Testing predictor contributions in sufficient dimension reduction
R. Dennis Cook
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Ann. Statist. 32(3): 1062-1092 (June 2004). DOI: 10.1214/009053604000000292


We develop tests of the hypothesis of no effect for selected predictors in regression, without assuming a model for the conditional distribution of the response given the predictors. Predictor effects need not be limited to the mean function and smoothing is not required. The general approach is based on sufficient dimension reduction, the idea being to replace the predictor vector with a lower-dimensional version without loss of information on the regression. Methodology using sliced inverse regression is developed in detail.


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R. Dennis Cook. "Testing predictor contributions in sufficient dimension reduction." Ann. Statist. 32 (3) 1062 - 1092, June 2004.


Published: June 2004
First available in Project Euclid: 24 May 2004

zbMATH: 1092.62046
MathSciNet: MR2065198
Digital Object Identifier: 10.1214/009053604000000292

Primary: 62G08
Secondary: 62G09 , 62H05

Keywords: central subspace , Nonparametric regression , sliced inverse regression

Rights: Copyright © 2004 Institute of Mathematical Statistics

Vol.32 • No. 3 • June 2004
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