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Viacúrovňová Monte Carlo simulácia×Simulácia Monte Carlo×
OdborBayesovské metódyRozhodovanie
RodinaBayesian methodsMCDM
Rok vzniku20081949
TvorcaMichael B. GilesMetropolis, N., Ulam, S.
Typvariance-reduction simulationRobustness wrapper — Monte Carlo uncertainty propagation
Pôvodný zdrojGiles, M. B. (2008). Multilevel Monte Carlo path simulation. Operations Research, 56(3), 607–617. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Ďalšie názvyMLMC, multilevel MC, multi-level Monte Carlo, MLMC simulation
Príbuzné40
ZhrnutieMultilevel Monte Carlo (MLMC) is a variance-reduction technique that estimates expectations by combining simulations run at multiple levels of numerical resolution. Coarse, cheap simulations capture most of the signal; fine, expensive simulations correct only the remaining small difference — dramatically reducing total computational cost compared with standard Monte Carlo at the finest level alone.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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ScholarGatePorovnať metódy: Multilevel Monte Carlo Simulation · MONTE-CARLO-SIMULATION. Získané 2026-06-18 z https://scholargate.app/sk/compare