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Simulations are carried out with alternative preferential patterns and rates of immigration.
This matrix can be configured in various ways to represent alternative preferential patterns.
A variety of evidence indicates that complex preferential patterns observed from fields are fractals.
The immigration rate is set at ϕ = 0.20 in Table 3, and simulation results for four preferential patterns are presented: indifference, isolation, partial discrimination, and adaptation.
We provide below examples of the P matrices for selected preferential patterns and the corresponding derived A matrices for two of our immigration simulation applications.
Like the power-law exponent, Gini coefficient can be used to measure the preferential patterns but in a more general way.
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Each preferential pattern results in an ultimate stable state for the proportionate population distribution as the number of generations increases without bound.
To modify a preferential pattern to accommodate supply restrictions but remain as close as possible to the original preferential distribution, we make use of a method known variously by the names biproportional adjustment, iterative proportional fitting, and others.
Our data suggest that matrix composition has an important role in EBs development and that it is possible to influence stem cell differentiation toward preferential pattern, by modulating the physical and biochemical properties of the scaffold.
Note that under the isolation preferential pattern there are no supply constraints the "demand" for and supply of young adult males are automatically in balance in each population, so the procedure we are about to describe is required only for other patterns.
M/N increases from the beginning, but the increases get smaller from one generation to the next, and for the adaptation preferential pattern, they are replaced by decreases, starting at t = 5, as the effects of indifference begin to offset the earlier effects of isolation in the adaptation process.
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