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From a Bayesian estimation perspective, it should be stressed that the simple movement model does not very accurately model the likelihoods of a person following different paths when comparing constrained and unconstrained starting points.
Since this is not true in the singlet model, the likelihoods under each model cannot match unless all the nucleotide frequencies are equal.
When we applied this version of the model, the likelihoods did not converge, even after running the maximum number of iterations allowed by the software (10,000).
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Given this model, the likelihood we are looking for (cf. (1)) can be expressed as (12).
In the post-2008 (including 2008) model, the likelihood ratio increased 8 units between the two models, which also shows little apparent improvement.
Using a multinomial logit model, the likelihood of farmers choosing different BUs was estimated using data from the 2007 National Farm Survey as a function of georeferenced habitat data.
For such a model, the likelihood function depends on at least one parameter that must be estimated.
Based on this simple model, the likelihood of the pedigree data was calculated under the assumption of multivariate normality.
The random model is the simplest model; the likelihood of any phrase occurring is independent of the identity of any preceding phrases.
It is a first-order Markov model and under this model, the likelihood of a phrase occurring depends on the identity of the previous phrase.
Contrary to expectations, after controls for the other variables in the model the likelihood to oppose FGM increases with age.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com