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作者:

Tian, Ruiqin (Tian, Ruiqin.) | Xue, Liugen (Xue, Liugen.) (学者:薛留根)

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EI Scopus

摘要:

A variable selection procedure is proposed using smooth-threshold generalized estimating equations based on quadratic inference functions (SGEE-QIF). The proposed procedure automatically eliminates inactive predictors by setting the corresponding parameters to be zero, and simultaneously estimates the nonzero regression coefficients by solving the SGEE-QIF. The proposed procedure avoids the convex optimization problem and is flexible and easy to implement. We establish the consistency and asymptotic normality of the resulting estimators. Extensive Monte Carlo simulation studies are conducted to examine the finite sample performance of the proposed variable selection procedure. © Springer-Verlag Berlin Heidelberg 2013.

关键词:

Convex optimization Intelligent systems Monte Carlo methods Sampling

作者机构:

  • [ 1 ] [Tian, Ruiqin]College of Applied Sciences, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing, 100124, China
  • [ 2 ] [Xue, Liugen]College of Applied Sciences, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing, 100124, China

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ISSN: 1865-0929

年份: 2013

卷: 391 PART I

页码: 100-109

语种: 英文

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