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Three distributions (Gamma, Gauss, and Poisson) for the explicit state duration modeling have been used, and a comparison between them has been reported.
The third-order Runge Kutta for time stepping, the fourth-order finite difference scheme for spatial derivatives and the fourth-order discretized Poisson for solving velocity are applied in present flow solver.
When the degree distribution is scale-free for the host and Poisson for the vectors the epidemic threshold decreases with the network size following a power-law, in agreement with the predictions made using Eq.1.
We caution against use of the Poisson for this analysis.
Logistic regression was used to estimate binary endpoints and Poisson for count endpoints.
Secondly, the Gamma distribution is a conjugate distribution of Poisson for the λ parameters.
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The user can choose the distribution with the slot model (1 for Poisson, 2 for Gaussian homoscedastic, 3 for negative binomial and 4 for segmentation of the variance).
Both approaches are compared for the Poisson equation for volume forms.
It provides accurate results but also requires computational (and implementational) effort for solving a Poisson equation for the pressure correction.
Considering Poisson arrivals for PUs, mathematical expressions for P Int are derived in [36] and [37].
Its speed-up was almost 12 times greater than for the direct Fast Poisson Solver for a single processor.
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