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Solidna mikrosymulacja×Symulacja Monte Carlo×
DziedzinaSymulacjaPodejmowanie decyzji
RodzinaProcess / pipelineMCDM
Rok powstania1990s–2000s1949
TwórcaBriggs, A. H.; O'Brien, B. J. and others in health technology assessment literatureMetropolis, N., Ulam, S.
TypSimulation with systematic robustness testingRobustness wrapper — Monte Carlo uncertainty propagation
Źródło pierwotneO'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 ↗
Inne nazwyRobust Micro-Simulation, Uncertainty-Robust Microsimulation, Probabilistic Microsimulation, Sensitivity-Enhanced Microsimulation
Pokrewne50
PodsumowanieRobust 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.
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ScholarGatePorównaj metody: Robust Microsimulation · MONTE-CARLO-SIMULATION. Pobrano 2026-06-15 z https://scholargate.app/pl/compare