Forecasting data with long multi-seasonal periods in the arima model using discrete fourier transform regressors
Time series data with multiple seasonalities often appear in data observed at high frequency. For instance, daily observed data may exhibit multiple seasonal patterns due to the combination of weekly, monthly, or annual periodicities. Traditional forecasting methods, such as the Autoregressive Integ...
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| Format: | Final Year Project / Dissertation / Thesis |
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2024
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| Online Access: | http://eprints.utar.edu.my/6859/ http://eprints.utar.edu.my/6859/1/YAP_YI_XIAN_FYP.pdf |