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However, mixture models of some suitable lifetime distributions, have the potential to highlight such interesting feature.
Theoretical Computer Science has brought to bear powerful ideas to find nearly optimal clusterings, while in Statistics mixture models of data have been useful in understanding the structure of data and in developing clustering algorithms.
As compared to simple models, the mixture models of underlying lifetime distributions are intuitively more appropriate and appealing to model the heterogeneous nature of process.
Constrained mixture models of arterial growth and remodeling (G&R) can facilitate the design of computational experiments which can bypass technical limitations in the laboratory, by considering illustrative special cases.
We submit that continuum-based constrained mixture models of arterial adaptation hold significant promise for deepening our basic understanding of arterial mechanobiology and thus for designing improved clinical interventions to treat many different types of arterial disease and injury.
The Gaussian mixture models of objects and background were then built under the Bayesian framework and the prior information on object shapes was introduced.
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Mazoyer, B. et al. Gaussian mixture modeling of hemispheric lateralization for language in a large sample of healthy individuals balanced for handedness.
The scope of this study is set for the mixture model of normal distributions with component specific variance, while the number of components is fixed.
Additionally, we propose a pseudo-relevance feedback algorithm based on the mixture modeling of the Dirichlet compound multinomial distribution to further improve retrieval accuracy.
The experimental design for the statistical optimization of the composite flour was carried out using optimum mixture model of response surface methodology.
The Mixture model of ANSYS Fluent has been used.
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