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Bayesian Scenario Analysis×Robustní analýza scénářů×
OborSimulaceSimulace
RodinaProcess / pipelineProcess / pipeline
Rok vzniku2000s1950 (foundations); 2003 (modern RDM formulation)
TvůrceDeveloped iteratively across Bayesian statistics and scenario planning communities; formalized in risk and decision analysis (Aven, Lempert et al., 2000s)Wald, A. (minimax foundation); Lempert et al. (RDM framework)
TypProbabilistic hybrid — Bayesian inference integrated with structured scenario analysisScenario-based robustness evaluation
Původní zdrojAven, T., & Reniers, G. (2013). How to define and interpret a probability in a risk and safety setting. Safety Science, 51(1), 223–231. DOI ↗Wald, A. (1950). Statistical Decision Functions. Wiley, New York. link ↗
Další názvyBSA, Bayesian scenario planning, probabilistic scenario analysis, Bayesian-weighted scenario analysisRSA, Robust Scenario Planning, Worst-Case Scenario Analysis, Minimax Regret Scenario Analysis
Příbuzné55
ShrnutíBayesian Scenario Analysis (BSA) combines structured scenario planning with Bayesian probability theory, assigning explicit prior probabilities to alternative futures and updating them as new evidence or expert judgments become available. The result is a probability-weighted distribution of outcomes across scenarios rather than a set of equally-weighted or arbitrarily-weighted futures.Robust Scenario Analysis evaluates a set of candidate strategies across a structured collection of plausible future scenarios and selects the strategy that performs acceptably well — or best in the worst case — regardless of which scenario materializes. It merges scenario planning with robustness criteria such as maximin, minimax regret, or satisficing to support decisions under deep, irreducible uncertainty.
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ScholarGatePorovnat metody: Bayesian Scenario Analysis · Robust Scenario Analysis. Získáno 2026-06-17 z https://scholargate.app/cs/compare