Comparer des méthodes

	MCO de Fourier (Moindres Carrés Ordinaires augmentés de termes de Fourier)	Moindres carrés ordinaires non linéaires (MCO non linéaires)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	2004	1974–1987
Auteur d'origine	Becker, Enders, and Hurn	Gallant (1987); Wooldridge (2010) for econometric treatment
Type	Augmented linear regression	Nonlinear regression estimator
Source fondatrice	Becker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899–906.	Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600
Alias	Fourier OLS, Fourier-augmented OLS, trigonometric OLS, smooth structural break OLS	nonlinear least squares, NLS, NLLS, nonlinear regression
Apparentées	6	5
Résumé	Fourier OLS is an OLS regression extended by adding low-frequency trigonometric (sine and cosine) terms to the regressor matrix. These Fourier components approximate smooth, gradual structural changes in the regression relationship over time without requiring knowledge of the number, timing, or form of the breaks.	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.