Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Робастное моделирование методом Монте-Карло× | Анализ чувствительности× | |
|---|---|---|
| Область≠ | Байесовские методы | Принятие решений |
| Семейство≠ | Bayesian methods | MCDM |
| Год появления≠ | 1990s–2000s | 2004 |
| Автор метода≠ | Saltelli, Rubinstein, and the uncertainty-quantification community | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. |
| Тип≠ | Robust simulation / uncertainty quantification | Robustness wrapper — parameter / weight perturbation sensitivity indices |
| Основополагающий источник≠ | Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M. & Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 978-0470059975 | Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. (2004). Sensitivity Analysis in Practice. Wiley, Chichester DOI ↗ |
| Другие названия≠ | robust MC simulation, Monte Carlo robustness analysis, robust stochastic simulation, uncertainty-robust Monte Carlo | — |
| Связанные≠ | 6 | 0 |
| Сводка≠ | Robust Monte Carlo simulation extends standard Monte Carlo by explicitly accounting for uncertainty in input distributions, model structure, or parameter assumptions. Rather than assuming a single fixed probability distribution for each input, the analyst considers a family of plausible distributions and evaluates how sensitive the output is to those choices, yielding conclusions that hold across a range of reasonable assumptions. | SENSITIVITY-ANALYSIS (Sensitivity Analysis — Systematic assessment of output variation w.r.t. input perturbations) is a ranking multi-criteria decision-making (MCDM) method introduced by Saltelli, A., Tarantola, S., Campolongo, F., Ratto, M. in 2004. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateНабор данных ↗ |
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