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We also simulated data for alternative parameter sets, and found that it is robust to most parameter choices (Additional file 3: Table S1).
In these cases, for most parameter choices, precision is close to 1.0, meaning every interaction predicted to be in the ancestor, in fact, was.
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Therefore, in Figure 5B, we plotted the single lowest containment fraction seen out of the 1000 computed; focusing on the single worst scenarios reveals a different picture, and shows that isolation of asymptomatic contacts and very high probabilities of finding workplace or social contacts would be needed to control smallpox under these most pessimistic parameter choices.
Elastic parameter choices are summarized in Supplementary Table 4.
Here, we consider the parameter choices we make.
Designs that lead to reproducing observed results independently of the parameter choice are the most likely to be good approximations to the real network structure.
This differs from past practice when model choice was conducted without statistical justification or by choosing the most parameter-rich model available [ 6, 8].
Most parameters involve keyboard interfacing.
Most parameters described are optimization parameters.
Our parameter choice endeavors to simulate Culex nigripalpus biology.
Parameter choice is done in the following way.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com