Σύγκριση μεθόδων

	Nonlinear OLS	Μη Γραμμικά Γενικευμένα Ελάχιστα Τετράγωνα (NGLS)
Πεδίο	Οικονομετρία	Οικονομετρία
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1974–1987	1975
Δημιουργός	Gallant (1987); Wooldridge (2010) for econometric treatment	Gallant (1975); extended by Davidson & MacKinnon
Τύπος	Nonlinear regression estimator	Nonlinear estimator
Θεμελιώδης πηγή	Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600	Gallant, A. R. (1987). Nonlinear Statistical Models. Wiley. ISBN: 978-0471802600
Εναλλακτικές ονομασίες	nonlinear least squares, NLS, NLLS, nonlinear regression	NGLS, nonlinear generalized least squares, feasible nonlinear GLS, FNGLS
Συναφείς	5	2
Σύνοψη	Nonlinear Ordinary Least Squares (NLS) estimates regression models in which the conditional mean function is nonlinear in the parameters. Like standard OLS it minimises the sum of squared residuals, but because no closed-form solution exists the estimator is found by iterative numerical optimisation. Under standard regularity conditions NLS is consistent and asymptotically normal.	Nonlinear Generalized Least Squares extends the classical GLS framework to regression models where the mean function is nonlinear in the parameters. It accounts for non-spherical errors — heteroscedasticity or autocorrelation — by pre-weighting the nonlinear objective with an estimated error covariance matrix, yielding consistent and asymptotically efficient estimates.