Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Pētījumi par tendenču simulācijas palīdzību× | Monte Carlo simulācija× | |
|---|---|---|
| Nozare≠ | Pētījuma dizains | Lēmumu pieņemšana |
| Saime≠ | Process / pipeline | MCDM |
| Izcelsmes gads≠ | 1990s–2000s (convergence of computational simulation with survey-based trend designs) | 1949 |
| Autors≠ | Synthesized from trend research (Creswell) and Monte Carlo / agent-based simulation traditions (Mooney, 1997) | Metropolis, N., Ulam, S. |
| Tips≠ | Quantitative research design with computational augmentation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Pirmavots≠ | Creswell, J. W., & Creswell, J. D. (2023). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE Publications. ISBN: 978-1071817971 | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Citi nosaukumi≠ | simulation-augmented trend study, Monte Carlo trend research, computational trend analysis, simulation-based longitudinal trend design | — |
| Saistītās≠ | 4 | 0 |
| Kopsavilkums≠ | Simulation-assisted trend research combines repeated cross-sectional survey data collected at multiple time points with computational simulation techniques — such as Monte Carlo methods or agent-based modeling — to project, validate, and stress-test observed trends. It extends classic trend research by replacing or supplementing extrapolation with probabilistic scenario modeling, allowing researchers to quantify uncertainty around trend trajectories and explore counterfactual futures under varying assumptions. | 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. |
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