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Bình phương tối thiểu trọng số phi tuyến (NWLS)×Bình phương tối thiểu có trọng số (WLS)×
Lĩnh vựcKinh tế lượngThống kê
HọRegression modelRegression model
Năm ra đời1960s–1980s (formalized in applied econometrics)1935
Người khởi xướngExtension of Gauss-Newton nonlinear least squares with Aitken-type weightingAlexander Craig Aitken
LoạiNonlinear regression estimatorWeighted linear estimator
Công trình gốcGreene, W. H. (2018). Econometric Analysis (8th ed.). Pearson Education. ISBN: 978-0134461366Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
Tên gọi khácNWLS, nonlinear weighted least squares, weighted nonlinear regression, heteroscedasticity-corrected nonlinear regressionWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squares
Liên quan33
Tóm tắtNonlinear Weighted Least Squares combines the flexibility of nonlinear regression with the variance-stabilizing power of observation-level weights. It minimises a weighted sum of squared residuals around a user-specified nonlinear mean function, making it the method of choice when the relationship is inherently nonlinear and error variance differs across observations.Weighted Least Squares is a generalization of Ordinary Least Squares (OLS) regression that assigns each observation a weight inversely proportional to its error variance, thereby down-weighting high-variance data points and up-weighting precise ones. Introduced in its general matrix form by Alexander Craig Aitken in 1935, WLS is the canonical remedy when heteroscedasticity is present and the error variance structure is known or can be reliably estimated.
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ScholarGateSo sánh phương pháp: Nonlinear WLS · Weighted Least Squares. Truy cập ngày 2026-06-18 từ https://scholargate.app/vi/compare