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Currently, StructuralIdentifiability estimates the identifiability of all initial conditions and parameters. If a parameter is known, it is easy to incorporate this through
si_ode =@ODEmodel(
X1'(t) = p - k1*X1(t),
X2'(t) =X1(t) -X2(t),
y1(t) =X2(t),
y2(t) = p
)
However, having certain initial conditions being known is very plausible (especially in cases where you set up the experiments yourself, such as in chemistry).
If #236 gets solved (but I have no idea how hard that would be though), this would automatically become possible through:
The functionality to add the known initial conditions (assuming that they are generic) has been added in release 0.5.4 (right now, for @ODEmodel macro only). An example is given in this tutorial
Currently, StructuralIdentifiability estimates the identifiability of all initial conditions and parameters. If a parameter is known, it is easy to incorporate this through
However, having certain initial conditions being known is very plausible (especially in cases where you set up the experiments yourself, such as in chemistry).
If #236 gets solved (but I have no idea how hard that would be though), this would automatically become possible through:
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