demodelr
2.0.1Simulating Differential Equations with Data
Overview
Designed to support the visualization, numerical computation, qualitative analysis, model-data fusion, and stochastic simulation for autonomous systems of differential equations. Euler and Runge-Kutta methods are implemented, along with tools to visualize the two-dimensional phaseplane. Likelihood surfaces and a simple Markov Chain Monte Carlo parameter estimator can be used for model-data fusion of differential equations and empirical models. The Euler-Maruyama method is provided for simulation of stochastic differential equations. The package was originally written for internal use to support teaching by Zobitz, and refined to support the text "Exploring modeling with data and differential equations using R" by John Zobitz (2021) https://jmzobitz.github.io/ModelingWithR/index.html.
Install
Health
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 75%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Downloads
Repository
Stars over time
Forks over time
Releases over time
Issues over time
Repository practices
4 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/jmzobitz/demodelr on 2026-07-31.
Dependencies
Nothing depends on this yet.
Code & Tests
Datasets
People & History
4 releases. Pick two to compare their code metrics. R releases are shown for context.
Package metadata
- First published
- 2022-06-23
- Total releases
- 4 / 4 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 3.9 KB / 7 files
- Download size
- 27 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet