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https://github.com/iliailmer/parameterestimation.jl

ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.
https://github.com/iliailmer/parameterestimation.jl

dynamical-systems julia julia-language mathematica-software mathematical-biology numerical-methods ode-model ordinary-differential-equations parameter-estimation parameter-identifiability symbolic-computation symbolic-numeric-computing

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ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.

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# ParameterEstimation.jl

[![Tests](https://github.com/iliailmer/ParameterEstimation.jl/actions/workflows/tests.yml/badge.svg)](https://github.com/iliailmer/ParameterEstimation.jl/actions/workflows/tests.yml) [![Documentation](https://github.com/iliailmer/ParameterEstimation.jl/actions/workflows/Documentation.yml/badge.svg)](https://github.com/iliailmer/ParameterEstimation.jl/actions/workflows/Documentation.yml)

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Symbolic-Numeric package for parameter estimation in ODEs

## Installation

Currently is installable via

```julia

using Pkg
Pkg.add(url="https://github.com/orebas/ParameterEstimation.jl")
```

The production version of this fork is installable via

```julia

using Pkg
Pkg.add("ParameterEstimation.jl")
```

## Toy Example

```julia
using ParameterEstimation
using ModelingToolkit

# Input:
# -- Differential model
@parameters mu
@variables t x(t) y(t)
D = Differential(t)
@named Sigma = ODESystem([D(x) ~ -mu * x],
t, [x], [mu])
outs = [y ~ x^2 + x]

# -- Data
data = Dict(
"t" => [0.000, 0.333, 0.666, 1.000],
x^2 + x => [2.000, 1.563, 1.229, 0.974])

# Run
res = estimate(Sigma, outs, data);
```