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Стохастична Марковська модель×Мікросимуляція×
ГалузьІмітаційне моделюванняІмітаційне моделювання
РодинаProcess / pipelineProcess / pipeline
Рік появи19931957
Автор методуMarkov, A. A. (probabilistic extension developed by Sonnenberg & Beck and others)Guy Orcutt (concept, 1957); modern tax-transfer frameworks developed through EUROMOD and related projects
ТипProbabilistic state-transition model with Monte Carlo uncertainty propagationPolicy simulation / computational social science
Основоположне джерелоSonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗O'Donoghue, C. (Ed.) (2014). Handbook of Microsimulation Modelling. Emerald. DOI ↗
Інші назвиProbabilistic Markov Model, Stochastic Markov Chain, SMM, Monte Carlo Markov ModelMikrosimülasyon, micro-simulation, policy microsimulation
Пов'язані65
ПідсумокA 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.Microsimulation is a computational method that simulates policy effects by operating directly on a population of individual micro-units — households, firms, patients — and applying rules to each unit according to its own demographic, economic, and behavioural characteristics. Developed conceptually by Guy Orcutt in 1957, it has become the standard tool for evaluating tax reform, pension systems, and health policy before implementation.
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ScholarGateПорівняння методів: Stochastic Markov Model · Microsimulation. Отримано 2026-06-15 з https://scholargate.app/uk/compare