J4 ›› 2012, Vol. 47 ›› Issue (3): 93-97.

• Articles • Previous Articles     Next Articles

Asymptotics for the LASSO estimator for partially linear models

LI Feng1, LU Yi-qiang2   

  1. 1. Resource & Economic Trade Department, Zhengzhou Institute of Aeronautical Industry Management,
      Zhengzhou 450015, Henan, China;
    2. Institute of Electronic Technology,  The PLA Information Engineering University, Zhengzhou 450004, Henan, China
  • Received:2011-04-10 Online:2012-03-20 Published:2012-04-01


 Based on the profile least squares method, the LASSO penalty profile least squares estimator is constructed, and the choices of penalty parameter and bandwidth are also discussed. Because the optimization problem is linear, it can be easily implemented. Under some regular conditions, the consistency and asymptotic normality of the estimator for parameter component are investigated. Finally, Monte Carlo simulation studies are conducted to assess the finite sample performance of the proposed variable selection procedures.

Key words: partially linear models; variable selection; asymptotics; LASSO

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