Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированное микромоделирование× | Модель Маркова× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1957 | 1906 |
| Автор метода≠ | Guy H. Orcutt | Andrei Markov |
| Тип≠ | Individual-level deterministic rule application | Probabilistic state-transition model |
| Основополагающий источник≠ | Orcutt, G. H. (1957). A new type of socio-economic system. Review of Economics and Statistics, 39(2), 116–123. DOI ↗ | Norris, J. R. (1997). Markov Chains. Cambridge University Press, Cambridge. ISBN: 9780521633963 |
| Другие названия | Arithmetic Microsimulation, Static Tax-Benefit Microsimulation, Deterministic Policy Simulation, Rule-based Microsimulation | Markov Chain, Discrete-Time Markov Chain, DTMC, Markov Process |
| Связанные | 5 | 5 |
| Сводка≠ | Deterministic Microsimulation applies a fixed set of policy rules or behavioral equations to each individual or household record in a microdata file, computing exact outcomes without any random sampling. It is the standard engine behind tax-benefit calculators and demographic projection models used by governments worldwide. | A Markov Model represents a system as a finite set of states and specifies the probability of moving from one state to another at each time step. By capturing only the current state — not the full history — it enables tractable analysis of complex dynamic processes across health economics, engineering reliability, operations research, and social-science modeling. |
| ScholarGateНабор данных ↗ |
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