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Regression model

逐步回归

逐步回归是一种用于多元线性回归的自动化变量选择程序,它根据统计标准(通常是 F 统计量或 p 值阈值)一次添加或删除预测变量。前向选择算法由 Efroymson (1960) 正式描述,双向变体由 Draper 和 Smith 在他们具有里程碑意义的 1966 年著作《回归分析应用》中推广。尽管该方法历史上被广泛使用,但现在已受到广泛批评,因此在其规范方法库中对其进行记录至关重要。

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来源

  1. Efroymson, M. A. (1960). Multiple regression analysis. In A. Ralston & H. S. Wilf (Eds.), Mathematical Methods for Digital Computers (pp. 191–203). Wiley. link
  2. Draper, N. R., & Smith, H. (1966). Applied Regression Analysis (1st ed.). Wiley. ISBN: 9780471221708
  3. Draper, N. R., & Smith, H. (1998). Applied Regression Analysis (3rd ed.). Wiley. ISBN: 9780471170822

如何引用本页

ScholarGate. (2026, June 3). Stepwise Variable Selection in Multiple Regression. ScholarGate. https://scholargate.app/zh/statistics/stepwise-regression

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被引用于

ScholarGateStepwise Regression (Stepwise Variable Selection in Multiple Regression). 于 2026-06-15 检索自 https://scholargate.app/zh/statistics/stepwise-regression · 数据集: https://doi.org/10.5281/zenodo.20539026