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ARGOS  

Automatic Regression for Governing Equations (ARGOS)
View on CRAN: Click here


Download and install ARGOS package within the R console
Install from CRAN:
install.packages("ARGOS")

Install from Github:
library("remotes")
install_github("cran/ARGOS")

Install by package version:
library("remotes")
install_version("ARGOS", "0.1.1")



Attach the package and use:
library("ARGOS")
Maintained by
Kevin Egan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-21
Latest Update: 2024-01-18
Description:
Comprehensive set of tools for performing system identification of both linear and nonlinear dynamical systems directly from data. The Automatic Regression for Governing Equations (ARGOS) simplifies the complex task of constructing mathematical models of dynamical systems from observed input and output data, supporting various types of systems, including those described by ordinary differential equations. It employs optimal numerical derivatives for enhanced accuracy and employs formal variable selection techniques to help identify the most relevant variables, thereby enabling the development of predictive models for system behavior analysis.
How to cite:
Kevin Egan (2023). ARGOS: Automatic Regression for Governing Equations (ARGOS). R package version 0.1.1, https://cran.r-project.org/web/packages/ARGOS. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.1.0 (2023-12-21 18:00)
Other packages that cited ARGOS R package
View ARGOS citation profile
Other R packages that ARGOS depends, imports, suggests or enhances
Complete documentation for ARGOS
Functions, R codes and Examples using the ARGOS R package
Some associated functions: alasso . argos . build_design_matrix . cubic2d_system . duffing_oscillator . lasso . linear2d_system . linear3d_system . lorenz_system . lotka_volterra . rossler_system . sg_optimal_combination . vdp_oscillator . 
Some associated R codes: argos_files.R .  Full ARGOS package functions and examples
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