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Generalized estimating equation (GEE) models with binomial distribution were used in the second approach, because they take the dependence observed between two values within a patient into account.
This information is one of randomly occurring coupling strength with binomial distribution.
Binary data with binomial distribution, Binomial(n = 1, P = 0.5).
This is a generalized linear model with binomial distribution family and identity link function [ 32].
This distribution has the expected average CpG methylation fraction a i /(a i + b i ), with variance decreasing as a i + b i increases, approaching a binomial distribution in the limit of large a i + b i.
In the large-N limit, such that all sequences of length l are likely to be realized, the out-degree distribution approaches a single binomial distribution (Fig. 4A).
Excellent agreements in branching dispersities between calculation with branching moments and prediction with assumption of binomial distribution for a tubular reactor and CSTR processes show that the branching distribution follows a binomial distribution for both processes.
For each experiment we used a Generalized Linear Mixed Model with a binomial distribution with log-link function.
In contrast, the in-degree distribution approaches a superposition of binomial distributions, with separate peaks corresponding to the number of different letters contained in a sequence of length l = 3 randomly sampled with replacement from the finite alphabet Π (Fig. 4B).
Determination of constitutive or differential expression of the RNA features was employed with baySeq [ 49], which uses an empirical Bayes approach assuming a negative binomial distribution and is capable of dealing with multi-group experimental designs.
The randomly changing coupling strength is considered with the concept of binomial distribution.
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