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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
Last synced: 2 days 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 (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-21T00:18:14.000Z (6 days ago)
- Last Synced: 2024-09-24T22:09:25.945Z (2 days 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: 6.22 MB
- Stars: 27
- Watchers: 6
- Forks: 8
- Open Issues: 16
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
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);
```