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Thus, they were estimated using the expectation-maximization estimation method.
Haplotype frequencies were estimated using the expectation-maximization approach implemented in the haplo.em function of haplo.stats v1.2.2 [47].
To this end, haplotype frequencies were estimated using the expectation-maximization algorithm [28] yielding all possible haplotypes present in our study population.
Haplotype frequencies were estimated using the expectation-maximization (EM) algorithm and association was evaluated by global and haplotype-specific score statistics [10].
Θ i is estimated using the expectation-maximization algorithm (EM) [ 60].
Haplotype frequencies were estimated using the expectation-maximization (EM) algorithm [ 36] implemented in Haploview 4.1.
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Next, the parameters θ of GMM are estimated using the Expectation Maximization algorithm [21].
For the two observation sequences and, the parameters of two GMMs are estimated using the expectation maximization (EM) algorithm [24].
To fit the Gaussians of the mixture model to the corresponding color histogram the parameters are estimated using the expectation maximization (EM) algorithm [24].
Model parameters are iteratively estimated using the expectation maximization (EM) algorithm [35], where the original parameters are refined to increase the likelihood of the estimated model for the observed feature vectors X, such that p ( X | λ ̄ ) ≥ p ( X | λ ).
A total of 133 HLA A-B haplotypes, 118 HLA B-DRB1 haplotypes and 173 HLA A-B-DRB1 haplotypes were estimated using the expectation maximization (EM) algorithm.
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