Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/asn074
Title: Model checking in regression via dimension reduction
Authors: Xia, Y. 
Keywords: Bootstrap
Crossvalidation
Goodness-of-fit
Kernel smoothing
Semiparametric model
Single-index model
Issue Date: Mar-2009
Citation: Xia, Y. (2009-03). Model checking in regression via dimension reduction. Biometrika 96 (1) : 133-148. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/asn074
Abstract: Lack-of-fit checking for parametric and semiparametric models is essential in reducing misspecification. The efficiency of most existing model-checking methods drops rapidly as the dimension of the covariates increases. We propose to check a model by projecting the fitted residuals along a direction that adapts to the systematic departure of the residuals from the desired pattern. Consistency of the method is proved for parametric and semiparametric regression models. A bootstrap implementation is also discussed. Simulation comparisons with several existing methods are made, suggesting that the proposed methods are more efficient than the existing methods when the dimension increases. Air pollution data from Chicago are used to illustrate the procedure. © 2009 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105222
ISSN: 00063444
DOI: 10.1093/biomet/asn074
Appears in Collections:Staff Publications

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