I tried 10^4 iterations, it threw a warning that it is not stable (?) I have 9 parameters, basically, it is a two-equations delay differential equation model, I am also trying to estimate the initial values and the coefficient of h(p, t), as well as the coefficient of other terms.
I tried to use SAMIN() for a simpler one, which only had two parameters, but it didn’t converge either.
I am just passing the norm of the difference between data and the mode, is it correct to do that? I tried the sum of squared errors, but it worked worse.
This is my model:
function G1_G2(du, u, h, p, t)
du = -p*(h(p, t-p)) + 2*p*(h(p, t-p)) - p*u
du = p*(h(p, t-p)) - p*(h(p, t-p)) - p*u
I have data for both u and u, I was giving both to the optimizer with
Dogleg() but here since it has to be a scalar, I am just passing norm of one of them.
Here is the summary: