Сравнение на методи

	Стохастична микросимулация	Стохастична системна динамика
Област	Симулационно моделиране	Симулационно моделиране
Семейство	Process / pipeline	Process / pipeline
Година на възникване	1957	1980s–2000s
Създател	Guy H. Orcutt	Jay W. Forrester (base SD); stochastic extensions developed through 1980s–2000s by multiple researchers
Тип	Stochastic individual-level simulation	Continuous stochastic simulation
Основополагащ източник	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Sterman, J.D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. Irwin McGraw-Hill. ISBN: 978-0072389159
Други названия	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	SSD, stochastic stock-flow modelling, probabilistic system dynamics, random system dynamics
Свързани	6	5
Резюме	Stochastic 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.	Stochastic System Dynamics (SSD) extends conventional system dynamics by replacing fixed parameter values and deterministic flow equations with probability distributions and random draws. Running many replications of the stock-flow model yields probabilistic trajectories — confidence bands rather than single lines — enabling rigorous uncertainty quantification and risk analysis in complex feedback systems such as epidemic models, supply chains, and energy policy scenarios.