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Fix example in docs and add documentation #33

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May 17, 2023
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Fix example in docs and add documentation #33

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6 changes: 6 additions & 0 deletions README.md
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Expand Up @@ -46,6 +46,10 @@ petabProblem = createPEtabODEProblem(bachmannModel,

After defining the parameter vector `θ`, you can compute the cost, gradient, and Hessian with the following code:

```julia
θ = petabProblem.θ_nominalT
```

```julia
# We only support in-place Hessian and gradients
∇f = zeros(length(θ))
Expand Down Expand Up @@ -75,6 +79,8 @@ Using this functionality, you can perform parameter estimation using optimizatio
* Handling pre-equilibration and pre-simulation conditions.
* Support for models with discrete events and logical operations.

## Documentation
Documentation and tutorials are available at https://sebapersson.github.io/PEtab.jl

## Development team

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