Salīdzināt metodes

	Stohastiskā mikrosimulācija	Monte Carlo simulācija
Nozare	Simulācija	Lēmumu pieņemšana
Saime	Process / pipeline	MCDM
Izcelsmes gads	1957	1949
Autors	Guy H. Orcutt	Metropolis, N., Ulam, S.
Tips	Stochastic individual-level simulation	Robustness wrapper — Monte Carlo uncertainty propagation
Pirmavots	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Citi nosaukumi	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	—
Saistītās	6	0
Kopsavilkums	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.	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.