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For some fixed model parameters, there are many feasible outcomes.

With model parameters, there are typically no opportunities to directly influence their variability.

Indeed, in our simulations the input never went far beyond the maximum for E. We then found that, for the standard choice of the model parameters, there is an additional stable equilibrium with high excitatory and low inhibitory activity.

These sensitivity analyses indicate that for each of our model parameters there is a threshold value below which no wave of infection is predicted during late summer, but above which a wave front will form and travel through the wild host population.

Although much data is referenced by the authors for the various model parameters, there is little biological justification presented for certain crucial modelling assumptions.

We would like to note here that due to the inherent high-dimensional nature of this analysis, based on varying six model parameters, there are many different possibilities for visualizing and reporting the outcomes.

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With uncertainty in model parameter, there is uncertainty in model structure.

The reason for using this model is that the model parameters considered there are less correlated and have biological meaning.

In addition to model parameter uncertainty, there are uncertainties with respect to the natural history of HPV, especially in older women, the nature of type-specific immunity following natural infection, and the relationships between different HPV types in the case of multiple infections.

Since all model parameters are constants, there is no meaning to examine the stationary and ergodic properties of this class of channel simulators.

Another problem with the two-mutation model is that when any of the model parameters are modified, there are relatively large fluctuations in the hazard function for carcinogenesis, which start almost as soon as the parameters are changed [ 4].

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