删失回归模型中的变量选择

Variable Selection for Censored Regression Models

  • 摘要: 在一个删失回归模型("Tobit"模型)中,我们常常要研究如何选择重要的预报变量.本文提出了基于信息理论准则的两种变量选择程序,并建立了它们的相合性.

     

    Abstract: In many situations, we are interested in selection of important variables which are adequate for prediction under a censored regression model (known as the " Tobit " model). In this paper, some selection procedures based on the information theoretic criteria are proposed, and these procedures are proved to be consistent.

     

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