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I've noticed that the choice of the default optimizer depends on whether the user passes a gradient function or not. However, if the user passes both function and gradient together in `fg!`, Optim def…
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**Submitting author:** @kanishkan91 (Kanishka Narayan)
**Repository:** https://github.com/JGCRI/ambrosia
**Version:** v1.3.0
**Editor:** @dhhagan
**Reviewers:** @tscheypidi, @sahilseth
**Managing EiC…
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Hey,
I'm getting type instability on the output of the Nelder-Mead optimization algorithm. Here is a simple example of the problem:
```
function bogus(x::Array{
> Body::Optim.MultivariateOptimi…
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Hi Eli
I'm pleased to have found your package cyclomort. I'm currently receiving the following warning messages when fitting the models:
> In sqrt(diag(solve(fits$hessian))) : NaNs produced
> I…
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Is it possible to add some better optimization method in traj.match()? I would recommend add genetic algorithm or alike method to make it better on finding global optimum.
Thanks a lot.
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```julia
f(x) = (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2
function g!(G, x)
G[1] = -2.0 * (1.0 - x[1]) - 400.0 * (x[2] - x[1]^2) * x[1]
G[2] = 200.0 * (x[2] - x[1]^2)
end
function h!(H, x)
…
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Currently it seems that there is no test that executes the post-processing twice from the same Python shell, that is, a test that does something like
```python
import cocopp
cocopp.main('slsqp*')…
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Is there a difference between Optim and Nlminb? I have noticed that Nlminb sometimes can optimise when Optim can't. If this happens are the results of Nlminb trustworthy?
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When finding parameters for ion channel models, we've generally been using the following approach:
```
repeat 25 times:
x = sample from (a meaningful!) prior
xbest, fbest = optimise(starting…
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NLopt is the optimizer used in the [`MixedModels`](https://github.com/JuliaStats/MixedModels.jl) package. Our tests have started failing under Julia-1.5.0-DEV and under
julia-nightly in a callback …