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This paper incorporates the maximum trimming likelihood estimation (Hadi and Luceño, 1997; Vandev and Neykov, 1998) in REML to obtain a robust estimation of modelling variance heterogeneity.
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The full system estimates are used for estimation of model parameters.
The estimation of model parameters reduces the modeling uncertainty and thus results in improving the tracking of interfacial boundary.
Modeling phase involves the selection of the modeling technique and the estimation of model's parameters.
Estimation of model parameters.
There are several methods for estimation of model parameters.
Estimation of model parameters via the method of maximum likelihood is presented in section 6.
The standard methodological rules apply in the estimation of Models (1) and (2).
There are possible endogeneity problems in the estimation of Model (2).
Table 5 presents the results from the probit estimation of model (2).
More information of parameter variation is needed for a more realistic estimation of model uncertainty, though.
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