robustness-check

Sensitivity analysis for dynamical systems tests parameter perturbations and equilibrium stability by generating tornado diagrams and phase-plane plots to identify which parameters have the largest impact on model outputs.

Model robustness under parameter uncertainty is checked using Monte Carlo simulations to quantify outcome variability under random parameter perturbations, producing reproducible robustness statistics and reports.

You can generate tornado diagrams and phase-plane plots for iterative models to visualize vector fields, equilibria, and trajectories, verifying that outputs remain stable when inputs vary within plausible ranges.

Reproducible sensitivity reports are prepared by running robustness checks on a base parameter set to generate plots and statistics, which can be included directly in methods sections and decision briefs.

Robustness analysis applies to climate and economic models by verifying that the model remains stable when inputs vary within plausible ranges and by quantifying outcome variability under random parameter perturbations.