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To stabilise the identification of the error model, transformations to the model residuals may be applied before identifying the model; #no
- no transformation
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- transforming the series by subtracting the mean
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- Box-Cox transformation, in this case the user must also identify the lambda parameter to be used. A lambda of zero indicates a natural logarithm transformation
Functionality described
This utility is applied to improve model time series predictions through combining modelled series and observed series. It uses as input an output series from a forecasting module (typically discharge from a routing or rainfall-runoff module) and the observed series at the same location. An updated series for the module output is again returned by the module. Updating is applied through application of an error model to the residuals between module output and observed series. This error model is applied also to the forecast data from this module to allow correction of errors in the forecast.
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