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GLS de Fourier (Mínims Quadrats Generalitzats de Fourier)×Mínims Quadrats Generalitzats (GLS)×
CampEconometriaEstadística
FamíliaRegression modelRegression model
Any d'origen2004-20121935
Autor originalBecker, Enders, and Hurn; extended by Enders and LeeAlexander Craig Aitken
TipusTime-series regression estimatorLinear estimator
Font seminalBecker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899-906. DOI ↗Aitken, A. C. (1935). IV.—On least squares and linear combination of observations. Proceedings of the Royal Society of Edinburgh, 55, 42–48. DOI ↗
ÀliesFourier GLS, Fourier-based GLS, Fourier flexible GLS, spectral GLSGLS, Aitken estimator, EGLS, feasible GLS
Relacionats13
ResumFourier GLS embeds low-frequency trigonometric (Fourier) terms into a generalized least squares framework to capture smooth, gradual structural change in a time series without requiring the researcher to specify when or how many breaks occurred. The approach is particularly valued in unit root testing and cointegration analysis where conventional break-date assumptions may be arbitrary.Generalized Least Squares (GLS) is a linear regression estimator that extends ordinary least squares to handle situations where the error terms are correlated or have non-constant variance (heteroscedasticity). Introduced by Alexander Craig Aitken in 1935, GLS achieves the Best Linear Unbiased Estimator (BLUE) under a general error covariance structure by weighting observations according to their precision, providing a theoretical bridge between OLS and modern linear mixed models.
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ScholarGateCompara mètodes: Fourier GLS · Generalized Least Squares. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare