This link between which quantities are observed and therefore which model parameters are held constant, is likely to have significant impact during the early stages of a disease outbreak in determining an appropriate response.
In our implementation, transition model parameters were held fixed over iterations; only emission model parameters were estimated from the data.
DACTAL also has potential advantages for datasets in which model parameters typically held fixed across the tree (such as the GTR matrix) are expected to vary (for example, due to changes in the GC content across the tree).
The concentrations of species Y i, Y i *, and the inhibitory drug D were normalized as follows: y i = [ Y i ] Y i T y i * = [ Y i * ] Y i T I = D T Y n T To determine if a detectable off-target effect occurred for a specific set of parameters, changes in the steady values of y2 and y 2 * were monitored as the model parameters were held fixed but I was varied from 10-4 to 10.
It is found that, at any time, the pressure drop of the two-fluid Casson model is considerably much lower than that of the two-fluid H-B model while all the other parameters held constant.
While many studies have examined the influence of specific experimental manipulations on the drift rate (e.g., changing perceptual salience; Ratcliff, 2002) or decisional processes (e.g., emphasizing speed vs. accuracy; Ratcliff, 2002), only a few studies have investigated individual differences in diffusion model parameters while holding task parameters constant.
The parametric sensitivity analysis was performed by perturbing each of the model parameters, while holding the rest constant.
For a sensitivity analysis focused on the model parameters, we hold the other model inputs (i.e. the model boundary conditions and the meteorological forcing) fixed.
Thus, parameter estimates listed in Tables 1 and 2 for parameters held constant across conditions reflect the best-fit parameters to the average data for the best-of-three model.
Following the preparation of predictive models relating input process parameters to corresponding output parameters, optimal input process parameters are determined using these models so that the output parameters hold within the target ranges.
