Порівняння методів

	Стохастичне мікромоделювання	Стохастичне дискретно-подієве моделювання
Галузь	Імітаційне моделювання	Імітаційне моделювання
Родина	Process / pipeline	Process / pipeline
Рік появи	1957	1960s–1970s
Автор методу	Guy H. Orcutt	Banks, Carson, Nelson, Nicol; Law, A. M.
Тип	Stochastic individual-level simulation	Stochastic simulation model
Основоположне джерело	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-Event System Simulation (5th ed.). Prentice Hall. ISBN: 9780136062127
Інші назви	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	Stochastic DES, SDES, Probabilistic DES, Monte Carlo DES
Пов'язані	6	6
Підсумок	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 Discrete-Event Simulation (Stochastic DES) models complex systems by advancing simulated time from one discrete event to the next, drawing event durations and inter-arrival times from fitted probability distributions. It is the standard technique for analyzing queues, manufacturing lines, healthcare pathways, and logistics networks under uncertainty, producing output statistics with confidence intervals.