Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Детерминированная Марковская модель× | Метод Монте-Карло× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Принятие решений |
| Семейство≠ | Process / pipeline | MCDM |
| Год появления≠ | 1993 | 1949 |
| Автор метода≠ | Sonnenberg, F. A. & Beck, J. R. | Metropolis, N., Ulam, S. |
| Тип≠ | Cohort state-transition model with fixed transition probabilities | Robustness wrapper — Monte Carlo uncertainty propagation |
| Основополагающий источник≠ | Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: a practical guide. Medical Decision Making, 13(4), 322–338. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Другие названия≠ | DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model | — |
| Связанные≠ | 5 | 0 |
| Сводка≠ | A Deterministic Markov Model is a cohort-level state-transition model in which all transition probabilities, state utilities, and costs are assigned single fixed values and the model is solved analytically in a single pass. Widely used in health technology assessment, policy analysis, and operations research, it traces a hypothetical cohort through mutually exclusive health or system states over discrete time cycles, accumulating expected outcomes such as quality-adjusted life years (QALYs) or costs. | 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. |
| ScholarGateНабор данных ↗ |
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