Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Робастное (устойчивое) микромоделирование× | Метод Монте-Карло× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Принятие решений |
| Семейство≠ | Process / pipeline | MCDM |
| Год появления≠ | 1990s–2000s | 1949 |
| Автор метода≠ | Briggs, A. H.; O'Brien, B. J. and others in health technology assessment literature | Metropolis, N., Ulam, S. |
| Тип≠ | Simulation with systematic robustness testing | Robustness wrapper — Monte Carlo uncertainty propagation |
| Основополагающий источник≠ | O'Brien, B. J., & Briggs, A. H. (2002). Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods. Statistical Methods in Medical Research, 11(6), 455-468. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Другие названия≠ | Robust Micro-Simulation, Uncertainty-Robust Microsimulation, Probabilistic Microsimulation, Sensitivity-Enhanced Microsimulation | — |
| Связанные≠ | 5 | 0 |
| Сводка≠ | Robust Microsimulation combines individual-level (micro) simulation with systematic uncertainty analysis — typically probabilistic sensitivity analysis — to generate outputs that are robust to parameter uncertainty, model structure assumptions, and input variability. It is widely used in health technology assessment, public policy, and social science to produce credible, decision-relevant predictions. | 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. |
| ScholarGateНабор данных ↗ |
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