An Extended Single‐index Model with Missing Response at Random |
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| Authors: | Qihua Wang Tao Zhang Wolfgang Karl Härdle |
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| Institution: | 1. Institute of Statistical ScienceShenzhen University;2. Academy of Mathematics and Systems SciencesChinese Academy of Sciences;3. School of ScienceGuangxi University of Science and Technology;4. School of BusinessSingapore Management University;5. Center for Applied Statistics and Economics (CASE), Humboldt‐Universit?t zu, Berlin |
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| 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 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. |
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| Keywords: | asymptotic normality estimating equations missing data single‐index models |
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