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Fourier ARMA model/Ushahidi
Rekodi ya ushahidi wa mbinu

Fourier ARMA model

The Fourier ARMA model augments the classical Autoregressive Moving Average framework with low-frequency Fourier (sine and cosine) terms to capture smooth, gradual shifts in the mean or trend of a time series. Unlike dummy-variable approaches, it requires no prior knowledge of when structural change occurred, approximating change with flexible trigonometric functions.

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Fourier-Augmented Autoregressive Moving Average Model
Rekodi ya mbinu ya kiajenda · regression-model / econometrics
  • Becker, R., Enders, W., & Hurn, S. (2006). A general test for time dependence in parameters. Journal of Applied Econometrics, 21(7), 1005–1028. · URL
  • 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
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Taxonomic bucketARIMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketARMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFourier ARDL Bounds Testmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketFourier VAR modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNonlinear ARMA modelmachine-suggested · Relational suggestion, not evidence.

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Sources recorded, not reviewed

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