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

Last synced: 3 months ago
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ParameterEstimation.jl is a Julia package for estimating parameters and initial conditions of ODE models given measurement data.

• Host: GitHub
• URL: https://github.com/iliailmer/parameterestimation.jl
• Owner: iliailmer
• License: gpl-3.0
• Created: 2022-11-15T15:33:18.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-03-27T00:21:03.000Z (3 months ago)
• Last Synced: 2025-04-02T05:33:50.664Z (3 months ago)
• Topics: 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
• Language: MATLAB
• Homepage: https://iliailmer.github.io/ParameterEstimation.jl/
• Size: 14.1 MB
• Stars: 27
• Watchers: 5
• Forks: 8
• Open Issues: 24
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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)

   


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);

```