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Estimation in semiparametric models using an auxiliary model |
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| Authors: | Stefan Huschens Gerhard Stahl |
| Institution: | 1. Fakult?t Wirtschaftswissenschaften Lehrstuhl für Quantitative Verfahren, insbesondere Statistik, Technische Universit?t Dresden, 01062, Dresden 2. Institut für international vergleichende Wirtschafts-und Sozialstatistik, Universit?t Heidelberg, Hauptstr 126, 69117, Heidelberg |
| Abstract: | Two classes of semiparametric and nonparametric mixture models are defined to represent general kinds of prior information. For these models the nonparametric maximum likelihood estimator (NPMLE) of an unknown probability distribution is derived and is shown to be consistent and relative efficient. Linear functionals are used for the estimation of parameters. Their consistency is proved, the gain of efficiency is derived and asymptotical distributions are given. |
| Keywords: | semiparametric model nonparametric maximum likelihood estimation auxiliary model |
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