Article (Scientific journals)
Robust estimation for ordinal regression
Croux, Christophe; Haesbroeck, Gentiane; Ruwet, Christel
2013In Journal of Statistical Planning and Inference, 143 (9), p. 1486–1499
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Keywords :
Breakdown point; Diagnostic plot; Influence function; Ordinal regression; Weighted Maximum Likelihood; Robust distances
Abstract :
[en] Ordinal regression is used for modelling an ordinal response variable as a function of some explanatory variables. The classical technique for estimating the unknown parameters of this model is Maximum Likelihood (ML). The lack of robustness of this estimator is formally shown by deriving its breakdown point and its influence function. To robustify the procedure, a weighting step is added to the Maximum Likelihood estimator, yielding an estimator with bounded influence function. We also show that the loss in efficiency due to the weighting step remains limited. A diagnostic plot based on the Weighted Maximum Likelihood estimator allows to detect outliers of different types in a single plot.
Disciplines :
Mathematics
Author, co-author :
Croux, Christophe ;  Université de Liège - ULiège > Département de mathématique > Département de mathématique
Haesbroeck, Gentiane ;  Université de Liège - ULiège > Département de mathématique > Statistique mathématique
Ruwet, Christel ;  Université de Liège - ULiège > Département de mathématique > Statistique mathématique
Language :
English
Title :
Robust estimation for ordinal regression
Publication date :
2013
Journal title :
Journal of Statistical Planning and Inference
ISSN :
0378-3758
Publisher :
Elsevier Science
Volume :
143
Issue :
9
Pages :
1486–1499
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 25 April 2013

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