analysis_summary

Creates a concise text summary of the analysis.

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.

José Mauricio Gómez Julián

EmpiricalDynamics

Empirical Discovery of Differential Equations from Time Series
Data

analysis_summary function

<dl><dt>results</dt>
<dd>Analysis results list.</dd>
<dt>verbose</dt>
<dd>Include additional details.</dd></dl>

Arguments

Create Analysis Summary — analysis_summary

<dl>

<dt>results</dt>
<dd>Analysis results list.</dd>


<dt>verbose</dt>
<dd>Include additional details.</dd>

</dl>

analysis_summary: Create Analysis Summary

Description

Usage

Value

Arguments