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Reactive structures have been characterized in a steady laminar, unidimensional mixing layer on a dense grid of parameters in moderate or intense low-oxygen dilution (MILD) combustion conditions with hot and diluted fuel.
We also tune using the same grid of parameters without the simplex method.
Iterations using a grid of parameters and initial conditions suggest that, for any parameter values, the frequencies f u, ij will converge for all initial conditions to a unique equilibrium denoted by the frequencies f ^ u, i j.
Furthermore, we use an initial bandwidth parameter h n as explained in Section 2.5, then searched over a grid of parameters (10[−0.5 0.1 0.5] for λ and h n ×[0.5, 1, 2, 5, 10, 50] for the bandwidth), and finally chose one that optimizes the BIC criterion defined in Section 2.5.
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By generating approximate likelihoods for the mean of observed summary statistics over a grid of parameter values, they determined that the Hausa best fit a growth model beginning ∼1,000 generations ago with a per-generation growth rate α of 0.75×10−3.
They do this for a grid of parameter values to estimate s and other parameters.
Simulation of all therapies on the discrete grid of parameter combinations.
We developed an innovative algorithm to solve this task: At first, we simulated a discrete grid of parameter values.
In summary, we parameterised the model by the following steps: Simulation of all therapies on the discrete grid of parameter combinations.
The reduction in number of parameters due to the use of the Pareto principle avoids the need for a multi-parameter cross-validation (for π, σ 1 2, and σ 2 2 ), which implies searching through a grid of parameter combinations.
We suspect that this small difference, which causes our demographic estimates to appear slightly conservative, probably occurs because we must calculate likelihoods at points along a grid of parameter values, rather than inferring them freely across the entire likelihood surface.
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