Sentence examples for likelihood itself from inspiring English sources

Note that the calculation of likelihood itself requires no assumptions on the relationships between variables.

In such situations, variational approaches can be applied, where a lower bound of the likelihood is maximized instead of the likelihood itself.

However, the empirical distributions of the likelihood itself varied significantly among different gene-pairs and thus we could not use a global distribution.

To find are (i) the highest likelihood among all possible mappings f (ii) the mapping f* with the highest likelihood itself, and (iii) the numbers of duplications in each tube d under the mapping f*.

While the parallelization of ML-based nucleotide- protein- and codon models has already been addressed (Stamatakis, 2011) (e.g. RAxML, IQPNNI, HyPhy), it has mostly been in the context of tree topology optimization, and not for the likelihood itself.

It is important to note that the maximum likelihood itself cannot be used as a score function, as without the inclusion of a penalty term it would always lead to selection of a completely connected network.

The h-likelihood itself is not an approximation but the adjusted profile h-likelihood given above is a first-order Laplace approximation to the marginal likelihood and gives excellent estimates for non-discrete distributions of y.

Note that this calculation of the impact of immigration on the joint likelihood is itself indirect.

The overall ALE likelihood score itself is not intended to be used to compare assemblies created from different datasets as is the case for the M_zebra_v0 (Illumina only) and M_zebra_UMD1 (Illumina + PacBio) assemblies.

For the likelihood function itself, p 0 and p t are nuisance (unobserved, latent state) parameters that need to be marginalized out by summing over all possible combinations of p 0 and p t.

Likelihood-based approaches have proven especially powerful for inferring phylogenetic trees [ 1, 2] but are computationally expensive owing both to the form of the likelihood function itself, and to the need to search the multidimensional space of possible outcomes (tree space) for optimal trees.