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Moreover, it is presented that both Freundlich and Langmuir isotherms can be used to fit the data and estimate model parameters; however, the overall data are slightly better fitted by Langmuir isotherm for both cations.
Sensitivity analysis demonstrated the importance of all four model parameters; however, to extend the model to other soils requires measurement of two parameters — cation exchange capacity and maximum fixation of ammonium in non-exchangeable form.
One of the model parameters, however, remains more uncertain than the rest.
The inclusion of the scaling parameter in the beta GEE has no impact on the estimation of the mean model parameters, however, it has the advantage that large estimates for ϕ can indicate heterogeneity in the data that is not accounted for by the model [ 3].
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Ultimately, there is a trade-off in the use of a simpler model with fewer parameters; however, a simpler model does not guarantee a better solution.
We have also considered a fully Bayesian model for all parameters; however this approach would require additional prior probability distributions for all parameters and the implementation of a simulation procedure such as Markov Chain Monte Carlo [ 36].
However, model parameters may not correlate very well with true physical characteristics of the concerned building.
We choose, however, model parameters (tau=10), (b=0.5), (beta_{mh}=0.1) and (beta _{hm}=0.1), and other parameters are fixed as in Table 3.
However, model parameters may not be precisely represented due to some factors in engineering practices, such as lack of sufficient data, data with fuzziness and unknown or non-constant reproduction conditions.
In the calibration process, the reduction in the RMSE value was particularly evident with the generalized mixed models for the other broadleaf species and other conifer species (21.0% and 13.0% respectively) compared with the generalized model fitted without random parameters; however, for the Pinus and Quercus groupings, the decrease in the value of this statistic was lower.
However, model parameters will be different, the consequences of which will be difficult to know without detailed studies.
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