Hi everyone,

I want to find the maximum of a function with the Optim.jl package, but I keep getting a DomainError. (I think Optim is trying to evaluate the log of a negative number)

```
using Optim, Interpolations
α = 0.4;
β = 0.96;
k = range(1e-3, 90.0, length = 1001) # grid on k
initial_v = 5 * log.(k.^α); #initial guess of value function evaluated at k
v_func = CubicSplineInterpolation(k, initial_v, extrapolation_bc = Line())
k_eval = k[1]
#Function to maximize (RHS of Bellman equation)
RHS(kprime) = -log(k_eval^α - kprime[1]) - β*v_func(kprime[1])
Optim.optimize(RHS, [k_eval]) #Getting a domain error
#Adding constraints to this univariate function
Optim.optimize(RHS, eps(1.0), 10000.0) #Domain error persists
```

For some reason, when I try to solve the **exact** same problem (for the economists out there, it’s the optimal growth model) but change what the maximization is done w.r.t., it’s able to find a solution.

```
#Trying alternative specification
RHS(c) = -log(c[1]) - β*v_func(k_eval^α - c[1])
Optim.optimize(RHS, [k_eval]) #solution successfully found
```

My two questions are:

- Is there any reason why the first approach ran into the DomainError while the second didn’t?
- Is there a way to avoid the DomainErrors?

Thank you!