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Fourier OLS (Fourier-Augmented Ordinary Least Squares)×Icke-linjär OLS (icke-linjära minsta kvadratmetoden)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår20041974–1987
UpphovspersonBecker, Enders, and HurnGallant (1987); Wooldridge (2010) for econometric treatment
TypAugmented linear regressionNonlinear regression estimator
UrsprungskällaBecker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899–906. DOI ↗Gallant, A. R. (1987). Nonlinear Statistical Models. John Wiley & Sons. ISBN: 978-0471802600
AliasFourier OLS, Fourier-augmented OLS, trigonometric OLS, smooth structural break OLSnonlinear least squares, NLS, NLLS, nonlinear regression
Närliggande65
SammanfattningFourier 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.
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ScholarGateJämför metoder: Fourier OLS · Nonlinear OLS. Hämtad 2026-06-19 från https://scholargate.app/sv/compare