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کمترین مربعات وزنی غیرخطی (NWLS)×حداقل مربعات تعمیم‌یافته (GLS)×
حوزهاقتصادسنجیآمار
خانوادهRegression modelRegression model
سال پیدایش1960s–1980s (formalized in applied econometrics)1935
پدیدآورExtension of Gauss-Newton nonlinear least squares with Aitken-type weightingAlexander Craig Aitken
نوعNonlinear regression estimatorLinear estimator
منبع بنیادینGreene, 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 ↗
نام‌های دیگرNWLS, nonlinear weighted least squares, weighted nonlinear regression, heteroscedasticity-corrected nonlinear regressionGLS, Aitken estimator, EGLS, feasible GLS
مرتبط33
خلاصهNonlinear 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.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.
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ScholarGateمقایسهٔ روش‌ها: Nonlinear WLS · Generalized Least Squares. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare