Alternatively, when the data D is considered fixed, p(D | θ) is regarded as a function of θ, and non-Bayesian methods such as maximum likelihood find the value of θ that maximizes p(D | θ) [ 1].
EM performs repeatedly between an expectation (E) step, an expectation of the likelihood of the observed variables, and maximization (M) step, which computes the maximum expected likelihood found on the E step.
After equilibration, the parallel tempering steps were all started from the same initial value, the maximum likelihood value found during the equilibration phase of the Monte Carlo procedure, and did not undergo any further switching between temperatures to ensure that the integration-over-temperatures interpretation of parallel tempering was valid.
The maximum likelihood solution finds the values (X_{q}) that maximize the probability in Eq. (7).
In comparison, Maximum Likelihood bootstrapping finds equivocal results for two of the three nodes (nodes II and III).
We use a method that combines the strengths of hidden Markov models and maximum likelihood to find relationships between drug/metabolite transporter families, and branches within families.
Maximum likelihood estimates were found by optimization over all four parameters simultaneously, using the optimize function found in the R package [ 24].
Bayesian and maximum likelihood phylogenetic analysis found that all viruses analyzed clustered in the genus Orthoreovirus, that reptile reoviruses formed three distinct clusters, and that an African grey parrot reovirus clustered with Nelson Bay virus from bats.
Finally, using a maximum likelihood estimator, they found the actual time of a change.
Consistent with our maximum likelihood analysis, we found a large number of invariant sites, in combination with highly variable sites (see Figure 2).
