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The expectation-maximization (EM) algorithm is often used to estimate model parameters of GMM by maximizing likelihood.
Although the model was fitted by maximizing likelihood under a Poisson spiking model, R 2 provides a more easily interpretable measure of performance.
We have presented a new probabilistic approach to genome assembly, maximizing likelihood in a model capturing essential characteristics of individual sequencing technologies.
After a signal change is detected, the estimated onset time t1 is found by maximizing likelihood estimators for each sample from last window position.
We used Newton's method used for minimizing least square criteria or for maximizing likelihood function and the iteration step can be written as [ 10], The solutions of the first and second order derivatives of the log-likelihood function, defined in Eq. (7), are given as The maximization process updates the new estimate λ ^ (k + 1 ) (x, y, z ) of the object function for iterative step k.
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Sample sites maximize likelihood of spatially and temporally uniform slopewash sedimentation.
Due to the complex relationship between acoustic features and contextual factors, it is extremely difficult to find the optimum sets of contextual regions that maximize likelihood for HMEM.
The determinants of unfavorable outcome should be investigated thoroughly to maximize likelihood of successful treatment.
For each spot, gels for excision were chosen based on maximum spot density in order to maximize likelihood of mass spectrometric detection.
With these values we compute the (maximized) likelihood (4).
Model training: First, a learning criterion is set up, which can either be to maximize likelihood or maximize posterior probability.
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