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Conventional mixture models such as rule-of-mixture model and Halpin Tsai model fail to explain the structure property regime in nanoscale at a high SWNT fraction ratio.

Site-heterogeneous mixture models such as "CAT" [ 48] (see Methods) efficiently deal with violations caused by high saturation levels [ 48, 49].

For metabolic networks, Markov mixture models, such as 3M, have been shown to provide an accurate and highly interpretable model of dominant pathways throughout a known network structure.

Mixture models such as Bayes B and Bayes C [ 41] assume that some fraction of the SNP have zero effect on the trait.

Markov mixture models such as 3M [ 9] directly search for dominant pathways within sequence data by assuming each mixture component is a Markov chain through a known network structure.

Theoretical justifications for 'large' mixture models such as this (in which the number of components in the mixture is larger than the true number of clusters in the data) are provided by Rousseau and Mengersen (2011).

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We believe that the integral image based EM algorithm could be applied to other tasks involving mixture model such as the GMM background modeling [32] in video processing.

An alternative method that we plan to explore is the infinite mixture model, such as a nonparametric Bayesian approach, which has been used previously in genomics research [ 17].

There are several challenges facing application engineers when estimate finite mixture models (FMMs), such as initialization of the expectation-maximization (EM) algorithm and determination of number of mixtures.

Probabilistic mixture distribution models such as the Mixed Rasch model (MRM; Rost, 1990) have not been used so far to test the psychometric qualities of PSDQ scores.

A clustering using a three component Gaussian Mixture Model confirmed such data separation.

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