plot_tvr_diagnostic

Produces a four-panel diagnostic plot showing the original series,
estimated derivative, reconstruction comparison, and residuals.

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

plot_tvr_diagnostic function

<dl><dt>Z</dt>
<dd>Numeric vector of original observations.</dd>
<dt>t</dt>
<dd>Numeric vector of time points.</dd>
<dt>dZ_tvr</dt>
<dd>TVR derivative object (from <code>compute_derivative_tvr</code>).</dd></dl>

Arguments

Diagnostic Plot for TVR Differentiation — plot_tvr_diagnostic

<dl>

<dt>Z</dt>
<dd>Numeric vector of original observations.</dd>


<dt>t</dt>
<dd>Numeric vector of time points.</dd>


<dt>dZ_tvr</dt>
<dd>TVR derivative object (from <code>compute_derivative_tvr</code>).</dd>

</dl>

plot_tvr_diagnostic: Diagnostic Plot for TVR Differentiation

Description

Usage

Value

Arguments