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Predicting Lake Levels by Exponential Smoothing
A statistical univariate forecasting technique called Exponentially Weighted Moving Average (EWMA) is used to obtain the estimates of future water levels of a large lake. The characteristics of the time series data consisting of average monthly lake levels is examined, and the parameters of the EWMA model are determined. The ex-post forecasts generated by this model are compared with the actual observations of lake water levels and with results obtained earlier with other stochastic methods. EWMA yields forecasts which are statistically indistinguishable from the actual observations.
Predicting Lake Levels by Exponential Smoothing
A statistical univariate forecasting technique called Exponentially Weighted Moving Average (EWMA) is used to obtain the estimates of future water levels of a large lake. The characteristics of the time series data consisting of average monthly lake levels is examined, and the parameters of the EWMA model are determined. The ex-post forecasts generated by this model are compared with the actual observations of lake water levels and with results obtained earlier with other stochastic methods. EWMA yields forecasts which are statistically indistinguishable from the actual observations.
Predicting Lake Levels by Exponential Smoothing
Koppula, Sivajogi D. (author)
Journal of the Hydraulics Division ; 107 ; 867-878
2021-01-01
121981-01-01 pages
Article (Journal)
Electronic Resource
Unknown
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