中国科学技术大学学报 ›› 2014, Vol. 44 ›› Issue (2): 101-105.DOI: 10.3969/j.issn.0253-2778.2014.02.004

• 原创论文 • 上一篇    下一篇

删失回归模型的分位数变量选择和压缩估计

叶仁玉   

  1. 1.安庆师范学院数学与计算科学学院, 安徽安庆 246133;2.中国科学技术大学管理学院统计与金融系, 安徽合肥 230026
  • 收稿日期:2012-07-09 修回日期:2012-12-10 出版日期:2014-02-28 发布日期:2014-02-28
  • 作者简介:叶仁玉,女,1977年生,硕士/副教授. 研究方向:数理统计. E-mail:yereny@163.com
  • 基金资助:
    安徽省教育厅高等学校自然科学基金(KJ2011A197,KJ2011B084)资助.

Variable selection and shrinkage quantile estimation for censored regression model

YE Renyu   

  1. 1.School of Mathematics and Computation Science, Anqing Teachers College, Anqing 246133, China; 2.Department of Statistics and Finance, School of Management, University of Science and Technology of China, Hefei 230026, China
  • Received:2012-07-09 Revised:2012-12-10 Online:2014-02-28 Published:2014-02-28

摘要: 删失回归模型是一种响应变量受限制的模型,广泛应用于计量经济学中. 针对删失回归模型,借助于分位数估计方法和SCAD型惩罚函数,提出了一种变量选择和压缩估计方法.该方法可选出对模型有贡献的回归变量,即非0回归系数,同时给出非零参数的一个相合估计. 另外,获得了变量选择方法的oracle性质.最后,利用数值模拟计算说明所提出方法的效果.

关键词: 删失回归模型, 分位数估计, SCAD, 变量选择, oracle性质

Abstract: Censored regression (“Tobit”) model is a kind of limited dependent variable model widely used in econometrics research. Based on the quantiles estimation and the smoothly clipped absolute deviation (SCAD), a method for variable selection and shrinking estimation was presented, which selects the non-zero coefficients corresponding to the significant variables and simultaneously gives a consistent estimate of the parameters. In addition, the variable selection possesses the oracle properties. Finally, numerical studies were conducted to evaluate the performance of the proposed method for censored regression model.

Key words: censored regression model, quantiles estimation, SCAD, variable selection, oracle property