Abstract
When we fit mechanistic models to data, we have to consider carefully the relationship between the nature of the data versus the nature of the model state variables. For example, when we work with continuous-time S(E)IR models it is important to keep in mind that incidence is not prevalence; so if our data is incidence we will need to do something more than trying to match simulated prevalence with observed incidence. We therefore start with a toy example using simulated data.
This chapter uses the following R-package: deSolve.
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If in a hurry we can ignore the constant and minimize \(\frac{n} {2} \log (RSS)\) because it is the relative likelihood that matters.
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Bolker (2008) is an excellent broad discussion on estimation for ecologically realistic models using a variety of methods.
- 3.
If the models are non-nested, formal tests are not available but information theoretical rankings of models using AIC, BIC, AIC-weights, etc. are useful.
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Bjørnstad, O.N. (2018). Trajectory Matching. In: Epidemics. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-97487-3_8
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