方法证据记录
Generalized Least Squares
Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Generalized Least Squares Estimator
分类方法记录 · regression-model / statistics
- 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
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