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Briefly, in order to infer the number of independent recombination events implied by a given data set, the RDP software [ 50] was used.
In this representation, nodes correspond to genes or proteins and the edges are weighted according to the evidence implied by a given data source for shared function of the connected nodes.
The total set of S. cerevisiae genes as defined by a given data set was reduced to the set of S. cerevisiae genes having K. waltii homologs (supplementary table S1, Supplementary Material online).
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The dichotomous logistic model according to Rasch (1960, 1966; henceforth denoted as Rasch Model, RM) allows for assessing its adequacy for describing a given data set by means of a conditional Likelihood Ratio Test (LRT; Andersen 1973).
Model hyper-parameter selection aims to find the parameters with the greatest generalization accuracy for a given data set by comparing the accuracy for different combinations of hyper-parameters.
One of the most important objectives of multivariate analysis is to separate the relevant signal from the noise part by using intrinsic variable correlations in a given data set.
Therefore, we could exclude, as previously shown [22], [24], that the PHI test is biased by the extent of heterogeneity within a given data set or that higher diversity and recombination values are due to rapid viral replication in disease tissues.
These weights are computed by a specific similarity metric for a given data source.
Courrieu et al. also proposed the Expected Correlation Validation Test (ECVT) to test whether the ICC method is valid for a given data set by comparing the expected and observed ICCs for different numbers of participants.
It is worthy of note that for a given data set, by definition, the F-statistic increases as the sample size increases with constant group means and standard deviations.
The parameter space is explored for each parameter by repeatedly fitting the model to a given data set, which then provides a likelihood-based confidence region for each parameter.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com