方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 确定性马尔可夫模型× | 蒙特卡洛模拟× | |
|---|---|---|
| 领域≠ | 仿真 | 决策 |
| 方法族≠ | Process / pipeline | MCDM |
| 起源年份≠ | 1993 | 1949 |
| 提出者≠ | Sonnenberg, F. A. & Beck, J. R. | Metropolis, N., Ulam, S. |
| 类型≠ | Cohort state-transition model with fixed transition probabilities | Robustness wrapper — Monte Carlo uncertainty propagation |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | DMM, Deterministic Markov Chain, Cohort Markov Model, Fixed-Parameter Markov Model | — |
| 相关≠ | 5 | 0 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|