I am trying to estimate the parameters for a delay differential equation. One of the parameters that I try to estimate is the (constant) delay itself. Following the tutorial documentation, I wrote the following code:

```
prob = DDEProblem(model, u0, h, tspan, p0[1:15], constant_lags=[p0[15]])
alg = MethodOfSteps(Tsit5())
sol = solve(prob,alg,saveat=time_points,abstol=1e-5,reltol=1e-5)
function problem_gen(prob,p)
u0 = [p[16]; 0.0; 0.0; data[1,1]; data[2,1]; (p[5] + p[6]*p[9])*p[8]]
h(p,t; idxs=nothing) = typeof(idxs) <: Number ? 0.0 : u0
new_prob = remake(prob;u0=u0,h=h,p=p[1:15],constant_lags=[p[15]])
end
function predict_dde(p)
prob_ = problem_gen(prob,p)
sol = solve(prob_,alg,saveat=1.0,abstol=1e-5,reltol=1e-5,
cb=PositiveDomain(zeros(6)))
Array(sol)
end
function loss_dde(p)
error = sum(abs2,data-predict_dde(p)[4:5,:])
end
cb = function (p,l...)
display(loss_dde(p))
return false
end
p_start = param_space[120,:]
cb(p_start,loss_dde(p_start))
result_dde = DiffEqFlux.sciml_train(loss_dde, p_start, ADAM(),
cb = cb, maxiters = 100)
```

When I run the code, I get the following error:

```
ERROR: MethodError: no method matching model(::Array{ReverseDiff.TrackedReal{Float64,Float64,ReverseDiff.TrackedArray{Float64,Float64,1,Array{Float64,1},Array{Float64,1}}},1}, ::ReverseDiff.TrackedArray{Float64,Float64,1,Array{Float64,1},Array{Float64,1}}, ::ReverseDiff.TrackedArray{Float64,Float64,1,Array{Float64,1},Array{Float64,1}}, ::ReverseDiff.TrackedReal{Float64,Float64,ReverseDiff.TrackedArray{Float64,Float64,1,Array{Float64,1},Array{Float64,1}}})
```

I was wondering if it is possible to do this estimation using `DiffEqFlux`

at all.

Many thanks in advance for any input!