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 didnâ€™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[1] = -p[1]*(h(p, t-p[5])[1]) + 2*p[2]*(h(p, t-p[6])[2]) - p[3]*u[1]
du[2] = p[1]*(h(p, t-p[5])[1]) - p[2]*(h(p, t-p[6])[2]) - p[4]*u[2]
end
```

I have data for both u[1] and u[2], 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: