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Kuadrat Terkecil Tertimbang Nonlinier (NWLS)×Kuadrat Terkecil Tertimbang (WLS)×
BidangEkonometrikaStatistika
KeluargaRegression modelRegression model
Tahun asal1960s–1980s (formalized in applied econometrics)1935
PencetusExtension of Gauss-Newton nonlinear least squares with Aitken-type weightingAlexander Craig Aitken
TipeNonlinear regression estimatorWeighted linear estimator
Sumber perintisGreene, 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 ↗
AliasNWLS, nonlinear weighted least squares, weighted nonlinear regression, heteroscedasticity-corrected nonlinear regressionWLS, weighted regression, heteroscedasticity-corrected OLS, variance-weighted least squares
Terkait33
RingkasanNonlinear 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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ScholarGateBandingkan metode: Nonlinear WLS · Weighted Least Squares. Diakses 2026-06-18 dari https://scholargate.app/id/compare