Performance of combined double seasonal univariate time series models for forecasting water demand
نویسنده
چکیده
In this article, we examine the daily water demand forecasting performance of double seasonal univariate time series models (Holt-Winters, ARIMA and GARCH) based on multi-step ahead forecast mean squared errors. A within-week seasonal cycle and a within-year seasonal cycle are accommodated in the various model speci cations to capture both seasonalities. We investigate whether combining forecasts from di¤erent methods for di¤erent origins and horizons could improve forecast accuracy. The analysis is made with daily data for water consumption in Granada, Spain.
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