قارن الطرق

	المربعات الصغرى المعممة غير الخطية (NGLS)	الانحدارات التي تبدو غير مترابطة (SUR)
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	1975	1962
صاحب الطريقة	Gallant (1975); extended by Davidson & MacKinnon	Arnold Zellner
النوع	Nonlinear estimator	System regression (multi-equation)
المصدر التأسيسي	Gallant, A. R. (1987). Nonlinear Statistical Models. Wiley. ISBN: 978-0471802600	Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368.
الأسماء البديلة	NGLS, nonlinear generalized least squares, feasible nonlinear GLS, FNGLS	SUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)
ذات صلة	2	5
الملخص	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.	Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS.