S.M. and J.B.K. analysed the model output and generated figures.
conceived the study, conducted the global model simulations, analysed the model output and wrote the paper.
J.J. and S.W. provided model output, and L.W. measured and analysed 14C.
Comparisons between model output and laboratory data are illustrated.
Other model parameters were obtained minimizing the residual sum of squares (RSS) between the model output and the experimental measurement, both on log scales.
For each model the squared error between the model output and the plant output is determined.
This RBFN-CA model is tested based on the comparison of model output and the real data.
In the case of the VC approach, the linear mixed model output and variance components estimates are also provided.
Secondly, relax the current tight linkage between statistical model output and required regulatory capital, incentivising prudent risk management through joint use of scenarios and control factors in addition to data-based statistical models in setting regulatory capital.
Using daily rather than fortnightly data for model calibration resulted in a large reduction in parameter-related uncertainty in model output and lower risk of obtaining unrealistic results.
The structure provides state estimates using a process model, the measured output, and the residual between the model output and the measured output.
