Regression model
广义最小二乘法 (GLS)
广义最小二乘法 (GLS) 是一种线性回归估计量，它扩展了普通最小二乘法，以处理误差项相关或具有非恒定方差（异方差性）的情况。GLS 由 Alexander Craig Aitken 于 1935 年引入，通过根据观测值的精度对其进行加权，在一般的误差协方差结构下实现了最优线性无偏估计量 (BLUE)，从而在 OLS 和现代线性混合模型之间架起了一座理论桥梁。
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来源
- Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI: 10.1017/S0370164600014346 ↗
- Greene, W. H. (2003). Econometric Analysis (5th ed.). Prentice Hall. ISBN: 978-0131108493
- Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586
如何引用本页
ScholarGate. (2026, June 3). Generalized Least Squares Estimator. ScholarGate. https://scholargate.app/zh/statistics/generalized-least-squares
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