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>.
Version: 1.0.1 Depends: R (≥ 4.1.0) Imports: ggplot2, purrr, tidyr, dplyr, formula.tools, GGally, rlang, utils, tibble Suggests: knitr, rmarkdown Published: 2022-09-16 DOI: 10.32614/CRAN.package.demodelr Author: John Zobitz [aut, cre] Maintainer: John Zobitz <zobitz at augsburg.edu> License: MIT + file LICENSE NeedsCompilation: no Materials: README, NEWS CRAN checks: demodelr results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=demodelr to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4