Sentence examples for by the same likelihood from inspiring English sources

Exact(1)

Firstly, they did not interpret in the same way 2 situations characterized by the same likelihood ratio, if inversed (versions A and B).

Similar(59)

Sorry but, strictly speaking, these mixed clades can also be explained (with the same likelihood) by an ancestral wide distribution followed by differential loss.

Thus, in this chapter, we argue that SCR and telemetry data can therefore be combined in the same likelihood by formally recognizing this distinction in the model.

Then PAUP* was used to calculate the same likelihoods using the optimal model parameters estimated by GARLI.

Now, we note that by the same logit transformations, the likelihood (data) distribution of the PURSUIT logit proportion corresponds to a normal distribution with a mean of −2.06 and a standard error of 0.163.

Moreover, there was no correlation between PT at first and second visits by the same infant, indicating the low likelihood that fixed infant characteristics affected PO success.

The corresponding log-likelihood is By the same reason as (10), we optimize the penalized "complete data" log-likelihood where g y jk | B s) is the analogue of f̂ (y jk| B s).

Unambiguously, all four studies found that the higher the prescribing volume of drugs by the same pharmaceutical company, the higher doctors' likelihood of early adoption of other drugs by that pharmaceutical company [ 27– 30].

If the event occurs in the j-th cell, not in the j-th cell, the difference in likelihood is given by the same formula with j in the place of j.

Victims of one type of crime are disproportionately likely to experience other types of crime (Feinberg 1980; Reiss 1980), so preventing one of those might reduce the likelihood of repeats by the same and different crime types which also squares with the crime drop being disproportionately a fall in repeat victimization (Britton et al. 2012; Ignatans and Pease, forthcoming).

This paper aims to compare a set of optimization techniques by consolidating them under the same maximum-likelihood (ML) framework.

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