An inverse problem is a collection of trials which define a multi-simulation optimization problem. The solution to an inverse problem are the "good parameters" which make the simulations simultaniously fit their respective data sufficiently well.
InverseProblem(trials, model, search_space)
InverseProblem stores the information needed to perform the optimization and find the
model parameters and/or initial conditions that best fit the data. The
model is an MTK
ODESystem describing the dynamics of the investigated system. The
trials constitute a collection that groups the individual trials according to their interpretation, such as
IndependentTrials (there is no link between trials) or
SteadyStateTrials (the first trial computes a steady state that other trials may continue to solve from).
search_space is a
Vector of pairs. Each pair consists of a parameter or initial condition to be optimized and its lower and upper bounds. When using an
search_space can hold distributions for each parameter instead of bounds, e.g. see
TransformedBeta or see the Distributions.jl documentation) for more options.