Package: EmpiricalDynamics
Title: Empirical Discovery of Differential Equations from Time Series
        Data
Version: 0.1.3
Authors@R: 
    person("José Mauricio", "Gómez Julián", email = "isadore.nabi@pm.me", role = c("aut", "cre"),
           comment = c(ORCID = "0009-0000-2412-3150"))
Description: A comprehensive toolkit for discovering differential and difference
    equations from empirical time series data using symbolic regression. The package
    implements a complete workflow from data preprocessing (including Total Variation
    Regularized differentiation for noisy economic data), visual exploration of
    dynamical structure, and symbolic equation discovery via genetic algorithms.
    It leverages a high-performance 'Julia' backend ('SymbolicRegression.jl') to provide
    industrial-grade robustness, physics-informed constraints, and rigorous
    out-of-sample validation. Designed for economists, physicists, and researchers
    studying dynamical systems from observational data.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
SystemRequirements: Julia (>= 1.6)
Depends: R (>= 4.0.0)
Imports: JuliaCall (>= 0.17), CVXR (>= 1.8), minpack.lm (>= 1.2),
        signal (>= 0.7), lmtest (>= 0.9), tseries (>= 0.10), ggplot2
        (>= 3.4.0), gridExtra (>= 2.3), stats, graphics, grDevices,
        utils, methods
Suggests: clarabel, scs, osqp (>= 1.0), ECOSolveR (>= 0.5), testthat
        (>= 3.0.0), knitr (>= 1.40), rmarkdown (>= 2.20), covr, mgcv
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/IsadoreNabi/EmpiricalDynamics
BugReports: https://github.com/IsadoreNabi/EmpiricalDynamics/issues
NeedsCompilation: no
Packaged: 2026-03-16 13:26:31 UTC; ROG
Author: José Mauricio Gómez Julián [aut, cre] (ORCID:
    <https://orcid.org/0009-0000-2412-3150>)
Maintainer: José Mauricio Gómez Julián <isadore.nabi@pm.me>
Repository: CRAN
Date/Publication: 2026-03-17 08:31:19 UTC
Built: R 4.6.0; ; 2026-04-28 17:02:19 UTC; unix
