Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Simulation Bootstrap× | Simulation de Monte-Carlo× | |
|---|---|---|
| Domaine≠ | Simulation | Prise de décision |
| Famille≠ | Process / pipeline | MCDM |
| Année d'origine≠ | 1979 | 1949 |
| Auteur d'origine≠ | Bradley Efron | Metropolis, N., Ulam, S. |
| Type≠ | Simulation-based nonparametric inference | Robustness wrapper — Monte Carlo uncertainty propagation |
| Source fondatrice≠ | Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Alias≠ | bootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling) | — |
| Apparentées≠ | 5 | 0 |
| Résumé≠ | Bootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly resampling with replacement from the observed data. Because it requires no parametric distributional assumptions, it provides a robust, general-purpose alternative to analytical confidence intervals and parametric hypothesis tests across continuous, ordinal, binary, and count data. | 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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