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部分线性模型的LASSO估计及其渐近性 被引量：2

Asymptotics for the LASSO estimator for partially linear models
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摘要 结合截面最小二乘估计思想,构造了LASSO惩罚截面最小二乘估计,并研究了惩罚参数和窗宽的选择问题。由于部分线性模型LASSO解仍为线性优化问题,因此容易实现。在一定条件下,本文还研究了参数估计量的相合性和渐近正态性。最后通过蒙特卡洛模拟研究了变量选择方法的小样本性质。 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.
作者 李锋 卢一强
机构地区 郑州航空工业管理学院经贸学院 中国人民解放军信息工程大学电子技术学院
出处 《山东大学学报（理学版）》 CAS CSCD 北大核心 2012年第3期93-97,共5页 Journal of Shandong University(Natural Science)
关键词 部分线性模型 变量选择 渐近分布 LASSO partially linear models variable selection asymptotics LASSO
分类号 O212.1 [理学—概率论与数理统计] O212.7 [理学—概率论与数理统计]
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参考文献17

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同被引文献19

  • 1Engle R F. Semiparametric estimates of the relation between weather and electricity sales[J].Journal of the American Statistical Association,1986.310-319.
  • 2T Hastie,R Tibshirani. Varying-Coefficient Models[J].Journal of the Royal Statistical Society - Series B: Statistical Methodology,1993.757-796.
  • 3Tibshirani R. Regression Shrinkage and selection via the Lasso[J].Journal of the Royal Statistical Society - Series B: Statistical Methodology,1996.267-288.
  • 4Schwarz G. Estimating the dimension of a model[J].Annals of Statistics,1978.461-464.
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  • 6HARDLE W, LIANG H, GAO J T. Partially Linear Models [M]. Heidelberg: Springer, 2000: 131-150.
  • 7XUE L G, ZHU L Z. Empirical likelihood semi parametric regression analysis for longitudinal data[J]. Biometrika, 2007, 94: 921-937.
  • 8FRANK 1, FRIEDMAN J. A statistical view Of some chemometrics regression tools with discussion) [J]. Tech.nometrics , 1993, 35: 109- 148.
  • 9TIBSHIRANI R. Regression shrinkage and selection via the lasso[J]. J R Stat Soc: Ser B, 1996, 58: 267-288.
  • 10ZOU H. The adaptive lasso and its oracle properties[J]. J Amer Statist Assoc, 2006, 101: 1418-1429.

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二级引证文献1

山东大学学报（理学版）
2012年 第3期

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