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Panel data estimation is used to estimate the two models.
The method of maximum likelihood estimation is used in estimating the parameters of the KGD.
We describe a parametric model to realize acoustic reverberation, and a statistical framework based on maximum likelihood estimation is used to estimate the model parameters.
Typically, a statistical measure such as Kurtosis or point spread function (PSF) estimation is used to estimate blurring or illumination degradation in the image.
First, the least squares estimation is used to estimate the constant concentration of protein x (without noise), given noisy measurement data of protein y.
Maximum likelihood estimation is used to estimate the unknown model parameters (λ0ij and βij) for each transition in the model together with their associated SEs.
Moreover, in multilevel analysis Maximum Likelihood estimation is used to estimate the variance components (Snijders and Bosker 1999; Laenen et al. 2006), which is the suitable method for naturalistic data such as ours (Crossley et al. 2007).
Maximum likelihood estimation is used to yield consistent parameter estimates.
GEE with robust variance estimation is used for obtaining these model-based estimates of the treatment effect and a simple test for appropriateness of the model is presented.
The MDOB is employed to estimate the disturbances of the closed-loop system, and the estimation is used for feedforward compensation design to reject disturbances.
The a b model provides the same estimate as the maximal chi-square method [35] when least squares estimation is used.
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