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Because models C1 and C2 represent simple modifications of model A we do not present these algebraically.
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Modifications of models source code must be easy and must not touch the main part of the source code.
These models, which are modifications of models previously available in the literature, are validated by the current experiments.
Two modifications of modelling the temperature dependence (with and without conservation of enthalpy) are introduced and studied quantitatively.
The heterogeneity in ω among sites was tested by comparing M0 and M3, and the positive selections were tested with three pairs of models, i.e., M1a and M2a, M7 and M8, M8a and M8, where M1a (nearly neutral) and M2a (positive selection) were slight modifications of models M1 (neutral) and M2 (selection) in Nielsen and Yang [56].
Assumptions for data modification −Which assumptions are related to the modification of model input?
In contrast, here we show that a straightforward modification of model (1 - 2) can lead to dynamical regimes that describe deterministic elimination of the tumor cells.
Hence modification of model via the removal of this interaction using backward elimination strategy improved the model (Equation 1). Figure 3A represents the three dimensional plot as function of temperature and inoculum size on lipase activity.
However, our model can still indirectly incorporate changes in trends in risk factors by appropriate modification of model probabilities that relate to risk of certain CHD events (eg for people currently with no history of CHD).
ii) The modifications to the basic model that allow for the imperfect detection of infection at the farm level (imperfect detection) or imperfect diagnostic test sensitivity at the sample level (imperfect sensitivity) do not improve model fit and although both result in some modification of model parameter estimates these remain within the ranges estimated from other plausible models.
In addition a new method for a fast generation and modification of simulation models is described.
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