পদ্ধতির তুলনা করুন

	স্টোকাস্টিক মাইক্রোসিমুলেশন	Stochastic Markov Model
ক্ষেত্র	অনুকরণ	অনুকরণ
পরিবার	Process / pipeline	Process / pipeline
উদ্ভবের বছর	1957	1993
প্রবর্তক	Guy H. Orcutt	Markov, A. A. (probabilistic extension developed by Sonnenberg & Beck and others)
ধরন	Stochastic individual-level simulation	Probabilistic state-transition model with Monte Carlo uncertainty propagation
মৌলিক উৎস	Orcutt, G. H. (1957). A new type of socio-economic system. The Review of Economics and Statistics, 39(2), 116–123.	Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338.
অপর নাম	Probabilistic Microsimulation, Monte Carlo Microsimulation, Stochastic Micro-simulation, SMSM	Probabilistic Markov Model, Stochastic Markov Chain, SMM, Monte Carlo Markov Model
সম্পর্কিত	6	6
সারসংক্ষেপ	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.	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.