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क्षेत्रअनुकरणनिर्णयन
परिवारProcess / pipelineMCDM
उद्भव वर्ष1990s–2000s1949
प्रवर्तकSaltelli, A. et al.; Claxton, K. et al. (health economics stream)Metropolis, N., Ulam, S.
प्रकारProbabilistic uncertainty quantification techniqueRobustness wrapper — Monte Carlo uncertainty propagation
मौलिक स्रोतSaltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli, D., Saisana, M., Tarantola, S. (2008). Global Sensitivity Analysis: The Primer. Wiley. ISBN: 9780470059975Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
उपनामPSA, Probabilistic Sensitivity Analysis, Stochastic SA, Monte Carlo Sensitivity Analysis
संबंधित50
सारांशStochastic Sensitivity Analysis (PSA) extends classical one-at-a-time sensitivity testing by representing uncertain model inputs as probability distributions and propagating them through the model via Monte Carlo sampling. The result is a full distribution of possible outputs, together with rankings of which inputs drive output variance the most — enabling robust, evidence-grounded conclusions under uncertainty.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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ScholarGateविधियों की तुलना करें: Stochastic Sensitivity Analysis · MONTE-CARLO-SIMULATION. 2026-06-18 को यहाँ से प्राप्त https://scholargate.app/hi/compare