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المحاكاة المجهرية العشوائية×نموذج ماركوف العشوائي×
المجالالمحاكاةالمحاكاة
العائلةProcess / pipelineProcess / pipeline
سنة النشأة19571993
صاحب الطريقةGuy H. OrcuttMarkov, A. A. (probabilistic extension developed by Sonnenberg & Beck and others)
النوعStochastic individual-level simulationProbabilistic state-transition model with Monte Carlo uncertainty propagation
المصدر التأسيسيOrcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123. DOI ↗Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗
الأسماء البديلةProbabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSMProbabilistic Markov Model, Stochastic Markov Chain, SMM, Monte Carlo Markov Model
ذات صلة66
الملخصStochastic Microsimulation tracks a large population of individual units — people, households, or firms — through time by applying random draws from empirically estimated probability distributions at each transition event. Unlike deterministic counterparts, every state change is decided by chance, preserving realistic heterogeneity and allowing rigorous uncertainty quantification across multiple simulation runs.A Stochastic Markov Model is a simulation technique that represents a system as a set of mutually exclusive health or decision states, moves a cohort (or individual agents) through those states using probabilistically sampled transition parameters, and aggregates outcomes across thousands of Monte Carlo iterations to produce full probability distributions over costs, outcomes, or rankings rather than single point estimates.
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ScholarGateقارن الطرق: Stochastic Microsimulation · Stochastic Markov Model. استُرجع بتاريخ 2026-06-17 من https://scholargate.app/ar/compare