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L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model

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Abstract

In this paper, the L 1-norm estimators and the random weighted statistic for a semiparametric regression model are constructed, the strong convergence rates of estimators are obtain under certain conditions, the strong efficiency of the random weighting method is shown. A simulation study is conducted to compare the L 1-norm estimator with the least square estimator in term of approximate accuracy, and simulation results are given for comparison between the random weighting method and normal approximation method.

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Authors and Affiliations

  1. College of Applied Sciences, Beijing University of Technology, Beijing 100022, China

    Liu-gen Xue

  2. Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing 100080, China

    Li-xing Zhu

  3. University of Hong Kong, Hong Kong, China

    Li-xing Zhu

Authors
  1. Liu-gen Xue
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  2. Li-xing Zhu
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Corresponding author

Correspondence to Liu-gen Xue.

Additional information

Supported by the Natural Science Foundation of Beijing City of China (1042002), the Science and Technology Development Foundation of Education Committee of Beijing City, the Special Expenditure of Excellent Person Education of Beijing (20041D0501515) and the grants (HKU7181/02H, HKU7060/04P) from Research Grants Council of Hong Kong, Hong Kong.

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Xue, Lg., Zhu, Lx. L 1-Norm Estimation and Random Weighting Method in a Semiparametric Model. Acta Mathematicae Applicatae Sinica, English Series 21, 295–302 (2005). https://doi.org/10.1007/s10255-005-0237-8

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  • DOI: https://doi.org/10.1007/s10255-005-0237-8

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