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We use a simulation platform that creates random arrivals of trade orders, that allows us to analyze subtle theoretical features of liquidity and price variability under various market structures.
To compare traditional statistics to ML approaches, we'll use a simulation of the expression of 40 genes in two phenotypes.
But if you are going to use a simulation, you want to have some reassurance that the results are valid.
Here, we use a simulation approach that overcomes these limitations by coupling a detailed hydrodynamic model that fully incorporates attenuation effects with vegetation rules based on preference to hydrodynamic conditions (see Methods section).
At George Mason University in Virginia, researchers measure the brain waves of study subjects as they use a simulation of the work done at the Nevada Air Force base.
Instead, they can use a simulation and a virtual model of a mobile robot F.A.A.K., which was designed at our department.
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In this paper, we use a simulation-based approach to deal with design problems in Bayesian hierarchical nonlinear (mixed-effects) models.
We use a simulation-based approach founded on Approximate Bayesian Computation, which allows for a thorough exploration of parameter space as well as the quantification of uncertainty around best estimates.
Moreover, we use a simulation-based method to estimate the state transition probability.
Instead of a traditional interpolation-based approach, we use a simulation-based approach that yields more robust extent estimates and quantified uncertainty.
We use a simulation-based model to study the impact of female philopatry and heterogeneity of habitat quality on the evolution of primary sex ratio.
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