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Wang, Qihua
Zhang, Tao
Härdle, Wolfgang Karl
Year of Publication: 
Series/Report no.: 
SFB 649 Discussion Paper 2014-003
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.
Missing data
Estimating equations
Single-index models
Asymptotic normality
Document Type: 
Working Paper

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