Variable Selection in High-dimensional Partially Linear Models
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摘要: 研究了高维部分线性模型中的变量选择,结合样条方法和Dantzig或Lasso变量选择方法,同时进行变量选择和未知参数估计,证明了估计误差的非渐近界.模拟结果说明,该方法在参数维数较高时优于已有方法.
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关键词:
- 样条 /
- 估计理论 /
- 线性回归 /
- MonteCarlo方法
Abstract: This paper considers the problem of variable selection in high-dimensional partially linear models.By combining spline method and Dantzig selector or Lasso,the authors simultaneously select variables and estimate parameters.The simulation results show that the proposed methods are better than the existing method when the dimension of parameters is much larger than the number of observation.-
Keywords:
- splines /
- estimation theory /
- linear regression /
- Monte Carlo method
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