Abstract
In modeling large complex systems, estimates for the model parameters cannot always be obtained by controlled experimentation or independent measurements. Moreover, most parameters are lumped parameters in the sense that they represent a wealth of underlying processes for which separate modeling is undesirable or impractical, so that their numerical value has a well-defined physical meaning only for the system under study within the context of the model specified. Consequently, some form of model calibration, achieved by adjusting the parameters in some way, is inevitable.
Keywords
- Maximum Likelihood Estimation
- Model Error
- Parameter Uncertainty
- Soluble Reactive Phosphorus
- Total Kjeldahl Nitrogen
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
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© 1983 International Institute for Applied Systems Analysis, Laxenburg/Austria
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van Straten, G. (1983). Maximum Likelihood Estimation of Parameters and Uncertainty in Phytoplankton Models. In: Beck, M.B., van Straten, G. (eds) Uncertainty and Forecasting of Water Quality. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-82054-0_6
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DOI: https://doi.org/10.1007/978-3-642-82054-0_6
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