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A mean of the 10 permuted matrices was estimated using CLUMPP (Jakobsson and Rosenberg 2007) and the LargeKGreedy algorithm.
To find the best mixture model of evolution, the number of general time reversible matrices was estimated by using a reversible-jump Markov chain Monte Carlo method (23 ).
Next, a matrix of pairwise geographic distances between populations was computed from geographic coordinates and the correlation between genetic and geographic matrices was estimated using 999 permutations in GenAlEx.
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The variance-covariance matrices were estimated with a Huber-type estimator that is robust for within-hospital clustering [ 32].
The initial probabilities and the covariance matrices are estimated similarly.
In this work, the percolation thresholds of dextromethorphan·HBr/Eudragit® RS-PM inert matrices were estimated.
The corresponding weight matrices are estimated, and utilized to estimate the underlying sources.
In such situation, if the BFR algorithm is applied, singular covariance matrices are estimated for some clusters.
Only in the last EM-iteration, the full covariance matrices are estimated for application in Equation (5).
First level individualized design matrices were estimated for each participant.
The covariance matrices were estimated using a recently described shrinkage approach [30], [31].
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