Global Sensitivity Analysis¶
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., et al. (2008). Global Sensitivity Analysis: The Primer. Wiley.
Cited by¶
7 citations across 7 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Ceteris Paribus
- In operations research it is one-at-a-time sensitivity analysis.
This sourceDefines one-at-a-time sensitivity analysis (varying one input with the others clamped) and contrasts it with global methods.
- In operations research it is one-at-a-time sensitivity analysis.
- Sensitivity Analysis (in Operations Research)
- The optimization output itself is often taken as authoritative without recognition of its parameter-conditionality, leading to over-confident decisions, misdirected information-gathering, and missed robustness concerns.
This sourceStandard primer covering screening, variance-based, and Monte Carlo methods for sensitivity analysis.
- The optimization output itself is often taken as authoritative without recognition of its parameter-conditionality, leading to over-confident decisions, misdirected information-gathering, and missed robustness concerns.
Mechanisms¶
- Inflation & Exchange-Rate Scenario Table
- Its strength is honesty about uncertainty: it replaces a single, over-confident figure with a defensible range and names the assumption the decision actually hinges on, which is exactly what basis uncertainty demands.
This sourceExplains how uncertainty analysis yields output ranges across plausible assumptions and sensitivity analysis identifies the inputs or assumptions that drive the result.
- Its strength is honesty about uncertainty: it replaces a single, over-confident figure with a defensible range and names the assumption the decision actually hinges on, which is exactly what basis uncertainty demands.
- Kernel Response Sensitivity Sweep
- Its failure mode is that a one-factor-at-a-time sweep can pronounce a kernel "robust" while missing fragilities that only emerge when parameters move together,
This sourceShows that one-at-a-time analysis can miss interactions and that sensitivity findings depend on the chosen input ranges and output of interest.
- Its failure mode is that a one-factor-at-a-time sweep can pronounce a kernel "robust" while missing fragilities that only emerge when parameters move together,
- Sensitivity Analysis
- The classic error is a one-at-a-time sweep that nudges each parameter around a single base case and declares the model robust — while missing interactions where two parameters are dangerous only in combination, exactly the regime a global, variance-based analysis is built to catch
This sourceShows that local one-factor perturbations around a base point can miss interaction effects that global variance-based sensitivity methods are designed to identify.
- The classic error is a one-at-a-time sweep that nudges each parameter around a single base case and declares the model robust — while missing interactions where two parameters are dangerous only in combination, exactly the regime a global, variance-based analysis is built to catch
- Sensitivity-to-Mapping-Change Review
- Its strength is exposing knife-edge preimages before they are trusted: a one-at-a-time sensitivity analysis
This sourceProvides one-at-a-time parameter-variation methods as part of sensitivity analysis.
- Its strength is exposing knife-edge preimages before they are trusted: a one-at-a-time sensitivity analysis
- Weight-Sweep Sensitivity Table
- Recompute and log outcomes. One-at-a-time moves show single-weight fragility; joint moves catch interactions the one-at-a-time view misses.
This sourceExplains how one-at-a-time analysis isolates individual-input effects and how joint or total-effect analysis reveals interactions it can miss.
- Recompute and log outcomes. One-at-a-time moves show single-weight fragility; joint moves catch interactions the one-at-a-time view misses.
Verification¶
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