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A key finding there was that modeling the distributions can be problematic, especially due to statistical outliers.
This is particularly relevant when modeling the distributions of expression of receptors, cytokine and signaling responses – an issue beyond the scope of this study.
We produced a second composite model by partitioning our presence data into the 15 recognized subspecies of P. polionotus and modeling the distributions of each subspecies separately.
Such a model is described by a partition of the vector into components C1, C2, and a pair of gaussian distributions g1, g2 modeling the distributions of C1, C2, respectively.
Building SDMs for P. polionotus by partitioning data into subspecies and building a composite distribution model mitigated the problem of high omission rates that usually occurs when modeling the distributions of widely distributed species.
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We utilized diagonal Gaussian mixture models (GMM) for modeling the distribution of each sound class.
The observations reported in this study set the foundations for modeling the distribution of event complexity.
There are two reasons for modeling the distribution with N μ, Σ.
A novel approach is proposed (vMF) for modeling the distribution of scatterers in space.
The geometric distribution has been used extensively in the literature in modeling the distribution of the lengths of waiting times.
Exercises are provided for modeling the distribution architecture for the Roadrunner Traffic Light Control System and the Coyote Unmanned Air Vehicle.
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