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Regression modelEconometrics / time series

Fourier ARMA-model

Fourier ARMA-modellen udvider det klassiske Autoregressive Moving Average-rammeværk med lavfrekvente Fourier-termer (sinus og cosinus) for at indfange glatte, gradvise skift i middelværdien eller trenden af en tidsserie. I modsætning til dummy-variabel-tilgange kræver den ingen forudgående viden om, hvornår strukturelle ændringer fandt sted, og approksimerer ændringer med fleksible trigonometriske funktioner.

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Kilder

  1. Becker, R., Enders, W., & Hurn, S. (2006). A general test for time dependence in parameters. Journal of Applied Econometrics, 21(7), 1005–1028. link
  2. Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. DOI: 10.1515/snde-2014-0101

Sådan citerer du denne side

ScholarGate. (2026, June 3). Fourier-Augmented Autoregressive Moving Average Model. ScholarGate. https://scholargate.app/da/econometrics/fourier-arma-model

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ScholarGateFourier ARMA model (Fourier-Augmented Autoregressive Moving Average Model). Hentet 2026-06-15 fra https://scholargate.app/da/econometrics/fourier-arma-model · Datasæt: https://doi.org/10.5281/zenodo.20539026