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The variable in this model is binary.
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The flaw detector model was binary, while the corrosion detector was binned into 10 percentile ranges.
Since the response variable in each model was binary, models were fit using a Bernoulli distribution and logit link.
The restriction site model was binary, similar to the F81 models of [37], and used the 'noabsencesite' sub-model of MrBayes.
Most of the independent variables in the model were binary while two were continuous (age in years and the European Index of the EQ-5D).
Greene [ 16] shows that estimators from the bivariate probit model become consistent and efficient when the dependent variables in the two-equation model are binary, and omitted variables are correlated with each other.
Third, the decision process in the previous model was binary: if the payoff to vaccinate exceeds the payoff not to vaccinate for an individual on a given day, s/he will always vaccinate and vice versa.
Since all models are binary classifiers that predict the coreceptor usage phenotype (X4-capable versus not X4-capable) from the genotype, the name of all models starts with geno2pheno-C.
However, this approach still uses discrete thresholds for activation of reactions that may not be consistent with experimental data, and the steady-state predictions of these models are binary [ 39].
The first model is the binary reception model employed by the Unit Disk Graph (UDG) model.
The proposed DLC model is a binary, non-convex, high dimension, combinatorial optimization problem, which is hard to be handled by the conventional programming methods.
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