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The estimation process yields maximum likelihood estimates for both (varGamma) and (sum).
However, the maximum likelihood estimates of σ2 are different.
Otherwise, stop; the last estimates are the maximum likelihood estimates. .
Maximum likelihood estimates of the model parameters are obtained.
Parameters expressed as maximum likelihood estimates (standardized solution).
The maximum likelihood estimates of the parameters in the model and their asymptotic properties are presented.
Under the normality assumption of errors, the least-squares estimates equal the maximum likelihood estimates.
We show maximum likelihood estimates (MLEs) of cell probabilities can be obtained in closed-form.
The derived pseudo-likelihood estimates in our study were therefore formally equivalent to the restricted likelihood estimates of the fixed and random effects that Martin et al.
The Laplace method, which produces approximate maximum likelihood estimates, was used as a fitting procedure.
The results of the maximum likelihood estimates derived from (18) are provided in Table 2.
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