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cff-version: 1.2.0
message: 'To cite package "EmpiricalDynamics" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'EmpiricalDynamics: Empirical Discovery of Differential Equations from Time
  Series Data'
version: 0.1.14
doi: 10.32614/CRAN.package.EmpiricalDynamics
abstract: 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.
authors:
- family-names: Gómez Julián
  given-names: José Mauricio
  email: isadore.nabi@pm.me
  orcid: https://orcid.org/0009-0000-2412-3150
repository: https://isadorenabi.r-universe.dev
repository-code: https://github.com/IsadoreNabi/EmpiricalDynamics
commit: 3f4ed02e4f72c5a78946652125333a4ba5f411e4
url: https://github.com/IsadoreNabi/EmpiricalDynamics
date-released: '2026-08-27'
contact:
- family-names: Gómez Julián
  given-names: José Mauricio
  email: isadore.nabi@pm.me
  orcid: https://orcid.org/0009-0000-2412-3150