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In this case, we resort to the GLRT ([30], Chap. 7) method, which consists of replacing the unknown parameters in the LLR by their maximum likelihood estimates.
Following the GLRT approach, the values of the unknown parameters required in (9) are substituted by their maximum likelihood estimates (MLE).
This obstacle is typically circumvented by adopting the GLRT approach, whereby the unknown parameters are substituted by their maximum likelihood estimates resulting in a simple and asymptotically optimal detector [32].
Similar(56)
Since the continuous-time Markov chains are probabilistic models it is possible to calculate likelihood estimates of various models and use these values to test their validity by comparing their maximum likelihood [22], [23].
These data sets were generated by taking real protein alignments and their maximum likelihood trees, and then simulating evolution of sites along that phylogenetic tree, treating it as ground truth.
This computational burden is reduced by estimating by maximum likelihood, that is, based on, and.
Given the basis patterns, we invert an observed image to deduce their coefficients by using maximum likelihood fitting for Poisson distributed uncertainties.
They have estimated their model by adopting maximum likelihood using an EM algorithm.
To detect the phylogenetic relationships in the orthologs under study, we obtained their phylogenetic trees by maximum likelihood with Phylip [ 21].
Model parameters were estimated by using the maximum likelihood method; their statistical significance was assessed by using the Wald statistic (8 ).
Parameters were estimated by maximum likelihood, and their variances were obtained from the observed information matrix.
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