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This function estimates ancestral character states by maximum likelihood optimization [ 45].
In these analyses, the GTR model was generally applied, with partition-wide estimates of the rate parameters by maximum likelihood optimization and empirical nucleotide frequency parameters.
Site-specific likelihoods were calculated by maximum likelihood optimization in Treefinder using the same model specifications as for phylogenetic inference [ 22].
Estimates of branch lengths were obtained from the concatenated matrix by maximum likelihood optimization using the GTR+G+I model in PAUP*, with all parameters estimated from the dataset.
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The trees resulting from maximum likelihood optimization for ORF5 and ORF7 respectively showed a strong clustering by farm.
An initial guess for the maximum likelihood optimization was set at 1.0 × 10−6.
Then it goes through a maximum likelihood optimization of the tree [21], [22].
We derived a maximum likelihood optimization approach allowing the estimation of the relative amplification efficiency of each allele.
Models were fitted by maximum likelihood nonlinear optimization from a heuristic starting point based on the character-independent birth-death model.
The model parameters were estimated by maximum likelihood (ML) optimization, using a dataset of presence-absence patterns of EF-1α and EFL.
The distributional parameters were estimated by maximum likelihood: numerical optimization was carried out using Nelder-Mead or Broyden-Fletcher-Goldfarb-Shanno methods for single and multi-parameter distributions, respectively [ 59].
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