Detailed outbreak data from Cairns was available for two dengue outbreaks (2003 and 2008/2009), hence one of the datasets (2003) was used to calibrate the model and the other dataset (2008/2009) to validate the overall model, including parameter choices arising from the calibration procedure.
Thus, our results could be generalized to other models and parameter choices depending on the locomotion system being modeled.
With a combination of analytical and numerical approaches, we demonstrate an optimal, one-to-one mapping between model parameters and choice probabilities even for tasks involving arbitrarily large numbers of alternatives.
Conclusions about the robustness of an optimal design against misspecification of model parameters and choice of optimality criterion are drawn based upon our results.
The only free model parameter remains the choice of γ, the ratio of wave height to water depth at initial breaking, and a well-established standard parameter is used for all model runs.
Our inferences were insensitive to model assumptions, priors, and parameter choices.
Extensive sensitivity analyses indicate that, while differences between model frameworks and alternative parameter choices make a difference, the economic impact of improved educational outcomes remains enormous.
Our basic model included several simplifying parameter choices, such as a lack of synaptic dynamics and a specific choice for the duration of the time window over which response magnitudes were computed (see Materials and Methods).
Uncertainties from model choice, model parameter, and measurement are explicitly included using probabilistic modeling.
Both simulations and on-line experiments with a pilot scale packed bed reactor for the partial oxidation of methanol have been used to study the effects of measurement choice, model parameter errors, and unmeasured process disturbances.
