Bayesian Bootstrap (Rubin)
Bayesian Bootstrap, introduceret af Donald B. Rubin i 1981, er en resampling-metode, der producerer en bayesiansk pendant til den frequentistiske bootstrap ved at tildele hver observation en tilfældig vægt trukket fra en Dirichlet-fordeling. Den giver en fuld posterior-fordeling for en statistik og tillader inkorporering af forhåndsviden.
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Method map
The neighbourhood of related methods — select a node to explore.
Kilder
- Rubin, D. B. (1981). The Bayesian Bootstrap. The Annals of Statistics, 9(1), 130-134. DOI: 10.1214/aos/1176345338 ↗
- Lo, A. Y. (1987). A Large Sample Study of the Bayesian Bootstrap. The Annals of Statistics, 15(1), 360-375. DOI: 10.1214/aos/1176350271 ↗
Sådan citerer du denne side
ScholarGate. (2026, June 1). Rubin's Bayesian Bootstrap. ScholarGate. https://scholargate.app/da/statistics/bayesian-bootstrap
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Blok-bootstrap (Moving Block og Stationary)Statistik↔ compare
- Bootstrap-inferensStatistik↔ compare
- Jackknife ResamplingStatistik↔ compare
- Permutationstest (Randomiseringstest)Statistik↔ compare
- Fisher Exact Randomization InferenceStatistik↔ compare
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