Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Odhad pomocí jackknife metody× | Simulace Monte Carlo× | |
|---|---|---|
| Obor≠ | Statistika | Rozhodování |
| Rodina≠ | Hypothesis test | MCDM |
| Rok vzniku≠ | 1956 | 1949 |
| Tvůrce≠ | Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming) | Metropolis, N., Ulam, S. |
| Typ≠ | Bias and variance estimation | Robustness wrapper — Monte Carlo uncertainty propagation |
| Původní zdroj≠ | Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360. DOI ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Další názvy≠ | delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme | — |
| Příbuzné≠ | 3 | 0 |
| Shrnutí≠ | Jackknife estimation is a classical resampling technique that computes the bias and variance of a statistical estimator by systematically leaving out one observation at a time and re-computing the statistic on each reduced sample. Introduced by Maurice Quenouille in 1956 for bias correction and extended by John Tukey in 1958 who coined the name, it is the historical predecessor of the bootstrap and remains analytically tractable for smooth, differentiable estimators. | 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. |
| ScholarGateDatová sada ↗ |
|
|