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We implemented the likelihood ratio test as an online tool (http://www.humangenomeprivacy.org/service.php) for participating teams to evaluate the privacy risks in their perturbed data.
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Severity was estimated by the use of the predicted mortality rate at ICU admissionfor every included patientby implementing the likelihood of death logit formule defined according to the APACHE II and SAPS II scores criteria and taking this cuantititative variable into account as a confounder factor in the regression model.
To compare the evolutionary pattern of tarantulas spider KTTs with others, we implemented the "maximum likelihood method" [26] to estimate the nonsynonymous/synonymous mutation ratio for the three clades ( Table S2, S3 and S4 in Supplemental Materials).
Researchers have implemented the maximum likelihood estimation (MLE) method in two popular commercial statistical software packages.
We implemented the maximum-likelihood and Bayesian methods by using PHYML (www.atgc-montpellier.fr/phyml/versions.php) and Mr. Bayes version 3.2 (http://mrbayes.scs.fsu.edu) software, respectively, for phylogenetic reconstructions.
Dougherty et al. [ 12] implemented the normalized maximum likelihood model to overcome this issue.
As in Ronald et al. [ 50], we implemented the branch-specific likelihood model with the codeml program in PAML 4.4 in our calculation.
Two approaches were implemented: firstly, the likelihood method of Goldman and Yang [ 26] and secondly, the Nei-Gojobori approach [ 27].
Two models are implemented in the likelihood framework, which accommodate coalescent events in the ancestral populations in a phylogeny of three species.
A critical rejection region was implemented on the likelihood distribution such that an individual genotype was excluded from a population if the likelihood fell below the α * 10, 000th lowest value of the distribution.
Carroll et al. [ 25] suggested the use of a Bayesian approach in order to avoid the complicated implementation of the Estimation-Maximization (EM) algorithm under a traditional frequentist analysis once the normal mixture model is implemented into the likelihood.
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