Functional hourly forecasting of water temperature
The paper describes the problem of forecasting water temperatures on an hourly basis using previous water and air temperatures as predictors. Both time series are decomposed using functional principal components, leading to low dimensional vector autoregressive modeling. The principal component scores mirror serial correlation, which is also incorporated in the model. The modeling exercise is motivated by and demonstrated with data collected in the German river Wupper, and the approach is contrasted to alternative routines which have been suggested in statistics and hydrology.
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- Hyndman, Rob J. & Shahid Ullah, Md., 2007.
"Robust forecasting of mortality and fertility rates: A functional data approach,"
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- Szymon Borak & Wolfgang Härdle & Enno Mammen & Byeong U. Park, 2007.
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SFB 649 Discussion Papers
SFB649DP2007-023, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Park, Byeong U. & Mammen, Enno & HÃ¤rdle, Wolfgang & Borak, Szymon, 2009. "Time Series Modelling With Semiparametric Factor Dynamics," Journal of the American Statistical Association, American Statistical Association, vol. 104(485), pages 284-298.
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