Regression modelEconometrics / time series

Fourier SARIMA modelis

Fourier SARIMA modelis paplašina klasisko sezonālo ARIMA sistēmu, iekļaujot trigonometriskus (Furjē) locekļus kā deterministiskus regresorus. Tas ļauj modelim tuvināt gludas, sarežģītas vai vairāku frekvenču sezonālās shēmas, neprasot pilnu sezonālo ARIMA struktūru katrai frekvencei, padarot to īpaši noderīgu augstas frekvences datiem vai sērijām ar nenegatīvu vai mainīgu sezonalitāti.

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Avoti

  1. Harvey, A., & Scott, A. (1994). Seasonality in dynamic regression models. The Economic Journal, 104(427), 1324-1345. link
  2. Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and Practice (2nd ed.). OTexts. link

Kā citēt šo lapu

ScholarGate. (2026, June 3). Fourier-augmented Seasonal Autoregressive Integrated Moving Average Model. ScholarGate. https://scholargate.app/lv/econometrics/fourier-sarima-model

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ScholarGateFourier SARIMA model (Fourier-augmented Seasonal Autoregressive Integrated Moving Average Model). Izgūts 2026-06-15 no https://scholargate.app/lv/econometrics/fourier-sarima-model · Datu kopa: https://doi.org/10.5281/zenodo.20539026