Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/91583
Authors: 
Wang, Qihua
Zhang, Tao
Härdle, Wolfgang Karl
Year of Publication: 
2014
Series/Report no.: 
SFB 649 Discussion Paper 2014-003
Abstract: 
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 iterative scheme 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 study is conducted to investigate the finite sample performances of the proposed estimators.
Subjects: 
Missing data
Estimating equations
Single-index models
Asymptotic normality
Document Type: 
Working Paper

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