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| Determinisztikus Szenzitivitásanalízis× | MONTE-CARLO-SIMULATION× | |
|---|---|---|
| Tudományterület≠ | Szimuláció | Döntéshozatal |
| Módszercsalád≠ | Process / pipeline | MCDM |
| Keletkezés éve≠ | 1950s–1970s (formalized) | 1949 |
| Megalkotó≠ | Saltelli, A. et al.; widely formalized across operations research and health economics | Metropolis, N., Ulam, S. |
| Típus≠ | Parameter variation / robustness testing | Robustness wrapper — Monte Carlo uncertainty propagation |
| Alapmű≠ | Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. ISBN: 9780470870938 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Alternatív nevek≠ | DSA, One-Way Sensitivity Analysis, Tornado Diagram Analysis, Parametric Sensitivity Analysis | — |
| Kapcsolódó≠ | 2 | 0 |
| Összefoglaló≠ | Deterministic Sensitivity Analysis (DSA) tests how model outputs change when individual or combined input parameters are varied across plausible ranges, one at a time or in structured combinations, without invoking probabilistic sampling. It is the standard approach in economic modeling, decision trees, and mathematical programming to identify which parameters drive conclusions and to demonstrate model robustness to regulators, reviewers, and stakeholders. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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