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An Extended Single‐index Model with Missing Response at Random
Author(s) -
Wang Qihua,
Zhang Tao,
Härdle Wolfgang Karl
Publication year - 2016
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/sjos.12233
Subject(s) - estimator , mathematics , curse of dimensionality , single index model , missing data , nonparametric statistics , index (typography) , statistics , algorithm , mathematical optimization , computer science , world wide web
An extended single‐index model is considered when responses are missing at random. A three‐step estimation procedure is developed to define an estimator for the single‐index parameter vector by a joint estimating equation. The proposed estimator is shown to be asymptotically normal. An algorithm for computing this estimator is proposed. This algorithm only involves one‐dimensional nonparametric smoothers, thereby avoiding the data sparsity problem caused by high model dimensionality. Some simulation studies are conducted to investigate the finite sample performances of the proposed estimators.