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While a good agreement can be found for models between groups, thanks to the existence of the IERS conventions, a great diversity still exist for parameter estimation, allowing possible future improvements in this direction.
Several techniques exist for parameter estimation (e.g., [22]).
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There exist a number of different optimization techniques for parameter estimation.
A Maximum Likelihood estimator was used for parameter estimation.
Two main cases of estimation procedures may be distinguished: the offline estimation procedure used for example for parameter estimation, and the online estimation procedure for control purposes.
Table 13.10: Data for parameter estimation exercise.
In order to increase efficiency and robustness for parameter estimation, there were 100 null trials included.
We justify a parametric bootstrap approximation that accounts for parameter estimation effects often ignored in practice.
Basic techniques for parameter estimation are tested.
For parameter estimation we found that cluster validity indices, the Davis Bouldin and Kim Ramakrishna indices in particular, are sufficient to estimate the parameters for most top clustering methods.
We then develop a procedure for parameter estimation that accounts for the confounding effect of background selection.
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