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Specifically, the proposed FCML-CP isuperioror to the commonly used statistical mixture likelihood approach using expectation maximization (EM) algorithm; it is much more time-saving especially.
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But in this study we will develop a mixture model-based likelihood approach to test the existence of a segregating QTL for power curves and estimate these curve parameters for different QTL genotypes.
Additionally, for amino acid alignments, we applied two programs: PhyloBayes [ 60], Bayesian approach and PhyML-CAT [ 61], maximum likelihood approach that use a mixture model describing across-site heterogeneities in the amino acid replacement patterns.
In [13], a maximum likelihood approach is proposed for two nonlinear mixtures of two texts, where the show-through nonlinearity is approximated as quadratic, and a blur kernel on the interfering pattern is accounted for and estimated.
The idea is to establish a mixture model M of K trees T k with a maximum likelihood approach (22).
Ecotype mixture proportions were estimated in the 2010 sample using the conditional maximum likelihood approach implemented in oncor (Kalinowski et al. 2007).
The maximum likelihood approach by Boussau et al. (2009) estimates the state space of an HMM (or of a mixture model) and also scales well with the number of taxa.
restricted maximum likelihood approach.
(2013) used the marginal maximum likelihood approach.
In this loop, the maximum likelihood approach is used (estimate).
We propose a maximum likelihood approach to this end.
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