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Spline Example: A Modulating Input Function
In this example, it is demonstrated how a continuous input function can be estimated that modulates the right-hand side of an ODE in a time-dependent manner. The model used for demonstration purpose is an SEIR model. These models are frequently applied for modelling of the dynamics of diseases in a population. The example shows how the modulation of the infection rate can be estimated. Such a modulation might originate from political actions that aim containment, i.e. reduction of the infection rate.
In particular, instead of a commont rate or reaction
Susceptibles -> Exposed CUSTOM "b * Infectious * Susceptibles" "description"
it might be desired to have time dependent b, e.g.
Susceptibles -> Exposed CUSTOM "b * b_time_dependence * Infectious * Susceptibles" "description"
The aim of this example is not having a realistic model and a common parametrization from literature. Instead, the model is rather simple for demonstrating capabilities of D2D in input estimation.
- Installation and system requirements
- Setting up models
- First steps
- Advanced events and pre-equilibration
- Computation of integration-based prediction bands
- How is the architecture of the code and the most important commands?
- What are the most important fields of the global variable ar?
- What are the most important functions?
- Optimization algorithms available in the d2d-framework
- Objective function, likelhood and chi-square in the d2d framework
- How to set up priors?
- How to set up steady state constraints?
- How do I restart the solver upon a step input?
- How to deal with integrator tolerances?
- How to implement a bolus injection?
- How to implement washing and an injection?
- How to implement a moment ODE model?
- How to run PLE calculations on a Cluster?